LEARNING COMPACT BINARY FACE DESCRIPTOR FOR FACE RECOGNITION
•Download as DOCX, PDF•
1 like•104 views
I3E Technologies, #23/A, 2nd Floor SKS Complex, Opp. Bus Stand, Karur-639 001. IEEE PROJECTS AVAILABLE, NON-IEEE PROJECTS AVAILABLE, APPLICATION BASED PROJECTS AVAILABLE, MINI-PROJECTS AVAILABLE. Mobile : 99436 99916, 99436 99926, 99436 99936 Mail ID: i3eprojectskarur@gmail.com Web: www.i3etechnologies.com, www.i3eprojects.com
Report
Share
Report
Share
Recommended
Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition
To perform unconstrained face recognition robust to variations in illumination, pose and expression, this paper presents a
new scheme to extract “Multi-Directional Multi-Level Dual-Cross Patterns” (MDML-DCPs) from face images. Specifically, the MDMLDCPs scheme exploits the first derivative of Gaussian operator to reduce the impact of differences in illumination and then computes the DCP feature at both the holistic and component levels. DCP is a novel face image descriptor inspired by the unique textural structure of human faces. It is computationally efficient and only doubles the cost of computing local binary patterns, yet is extremely robust to pose and expression variations. MDML-DCPs comprehensively yet efficiently encodes the invariant characteristics of a face image from multiple levels into patterns that are highly discriminative of inter-personal differences but robust to intra-personal variations.
Experimental results on the FERET, CAS-PERL-R1, FRGC 2.0, and LFW databases indicate that DCP outperforms the state-of-the-art local descriptors (e.g. LBP, LTP, LPQ, POEM, tLBP, and LGXP) for both face identification and face verification tasks. More impressively, the best performance is achieved on the challenging LFW and FRGC 2.0 databases by deploying MDML-DCPs in a simple recognition scheme.
An improved double coding local binary pattern algorithm for face recognition
Abstract A human face conveys a lot of information about the identity and emotional state of the person. So now a day’s face recognition has become an interesting and challenging problem. Face recognition plays a vital role in many applications such as authenticating a person, system security, verification and identification for law enforcement and personal identification among others. So our research work mainly consists of three parts, namely face representation, feature extraction and classification. The first part, Face representation represents how to model a face and check which algorithms can be used for detection and recognition purpose. In the second phase i.e. feature extraction phase we compute the unique features of the face image. In the classification phase the computed DLBP face image is compared with the images from the database. In our research work, we use Double Coding Local Binary Patterns to evaluate face recognition which concentrate over both the shape and texture information to represent face images for person independent face recognition. The face area is firstly cut into small regions from which Local Binary Patterns (LBP), then we compute histograms to generate LBP image then we compute single oriented mean image from which we again compute histogram values small regions and at last concatenated into a single feature vectors and generate D-LBP image. This feature are used for the representation of the face and to measure similarities between images. Keywords: local binary pattern (LBP), double coding local binary pattern (D-LBP), features extraction, classification, pattern recognition, histogram, feature vector.
Illumination Invariant Face Recognition System using Local Directional Patter...
The document proposes an illumination-robust face recognition system using local directional pattern (LDP) images and two-dimensional principal component analysis (2D-PCA). It extracts LDP images from face images as inputs to 2D-PCA for feature extraction, instead of using LDP for histogram feature extraction like previous works. Experimental results on the Yale B and CMU-PIE databases show the proposed approach achieves higher recognition accuracy than PCA and LBP-based methods, demonstrating its effectiveness in handling illumination variations. The maximum recognition rates are 96.43% for Yale B and 100% for CMU-PIE illumination sets.
Performance Evaluation of Illumination Invariant Face Recognition Algorthims
This document presents a performance evaluation of illumination invariant face recognition algorithms. It proposes a hybrid approach using Local Binary Pattern and Local Ternary Pattern fusion with gradient-based illumination normalization. The performance is evaluated using Receiver Operating Characteristics (ROC) curves and the proposed algorithm is shown to outperform traditional algorithms like Gradientfaces and Weberface on benchmark databases by achieving a higher true positive rate and lower false positive rate.
IRJET- Analysis of Face Recognition using Docface+ Selfie Matching
1. The document proposes a method called DocFace+ to automatically match ID document photos to selfie images in real-time with high accuracy.
2. It uses transfer learning by fine-tuning a base model trained on unconstrained face images on a private ID-selfie dataset. A pair of sibling networks are used to learn unified face representations.
3. Experimental results on an ID-selfie dataset show the proposed DocFace+ system achieves better generalization performance than publicly available general face matchers.
tScene classification using pyramid histogram of
This document proposes a new method called Pyramid Histogram of Multi-scale Block Local Binary Pattern (PH-MBLBP) for scene classification. PH-MBLBP encodes both micro- and macro-structures of image patterns to provide a more complete representation than basic LBP. It divides images into spatial regions at multiple resolutions to capture geometric information. Experiments on 15 scene categories show PH-MBLBP outperforms SIFT and provides a powerful yet fast texture descriptor for scene recognition.
Modified CSLBP
Image hashing is an efficient way to handle digital data authentication problem. Image hashing represents quality summarization of image features in compact manner. In this paper, the modified center symmetric local binary pattern (CSLBP) image hashing algorithm is proposed. Unlike CSLBP 16 bin histogram, Modified CSLBP generates 8 bin histogram without compromise on quality to generate compact hash. It has been found that, uniform quantization on a histogram with more bin results in more precision loss. To overcome quantization loss, modified CSLBP generates the two histogram of a four bin. Uniform quantization on a 4 bin histogram results in less precision loss than a 16 bin histogram. The first generated histogram represents the nearest neighbours and second one is for the diagonal neighbours. To enhance quality in terms of discrimination power, different weight factor are used during histogram generation. For the nearest and the diagonal neighbours, two local weight factors are used. One is the Standard Deviation (SD) and other is the Laplacian of Gaussian (LoG). Standard deviation represents a spread of data which captures local variation from mean. LoG is a second order derivative edge detection operator which detects edges well in presence of noise. The proposed algorithm is resilient to the various kinds of attacks. The proposed method is tested on database having malicious and non-malicious images using benchmark like NHD and ROC which confirms theoretical analysis. The experimental results shows good performance of the proposed method for various attacks despite the short hash length.
Dynamic Error Concealment Algorithm for Multiview Coding Using Lost MBs Size...
The document proposes an adaptive error concealment algorithm for multiview video coding that exploits spatial, temporal, and inter-view information. For intra macroblocks, a Spatial-Inter View algorithm is used to conceal errors using weighted pixel averaging and disparity vectors from other views. For inter macroblocks, the algorithm adaptively selects candidate macroblocks for replacement based on the size of the lost macroblock and the view of the reference frame, generating additional candidates to find better matches. Simulation results show the proposed algorithm achieves up to 12.4 dB and 0.73 dB higher PSNR than applying no error concealment or a normal algorithm, respectively, with better subjective quality and lower complexity.
Recommended
Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition
To perform unconstrained face recognition robust to variations in illumination, pose and expression, this paper presents a
new scheme to extract “Multi-Directional Multi-Level Dual-Cross Patterns” (MDML-DCPs) from face images. Specifically, the MDMLDCPs scheme exploits the first derivative of Gaussian operator to reduce the impact of differences in illumination and then computes the DCP feature at both the holistic and component levels. DCP is a novel face image descriptor inspired by the unique textural structure of human faces. It is computationally efficient and only doubles the cost of computing local binary patterns, yet is extremely robust to pose and expression variations. MDML-DCPs comprehensively yet efficiently encodes the invariant characteristics of a face image from multiple levels into patterns that are highly discriminative of inter-personal differences but robust to intra-personal variations.
Experimental results on the FERET, CAS-PERL-R1, FRGC 2.0, and LFW databases indicate that DCP outperforms the state-of-the-art local descriptors (e.g. LBP, LTP, LPQ, POEM, tLBP, and LGXP) for both face identification and face verification tasks. More impressively, the best performance is achieved on the challenging LFW and FRGC 2.0 databases by deploying MDML-DCPs in a simple recognition scheme.
An improved double coding local binary pattern algorithm for face recognition
Abstract A human face conveys a lot of information about the identity and emotional state of the person. So now a day’s face recognition has become an interesting and challenging problem. Face recognition plays a vital role in many applications such as authenticating a person, system security, verification and identification for law enforcement and personal identification among others. So our research work mainly consists of three parts, namely face representation, feature extraction and classification. The first part, Face representation represents how to model a face and check which algorithms can be used for detection and recognition purpose. In the second phase i.e. feature extraction phase we compute the unique features of the face image. In the classification phase the computed DLBP face image is compared with the images from the database. In our research work, we use Double Coding Local Binary Patterns to evaluate face recognition which concentrate over both the shape and texture information to represent face images for person independent face recognition. The face area is firstly cut into small regions from which Local Binary Patterns (LBP), then we compute histograms to generate LBP image then we compute single oriented mean image from which we again compute histogram values small regions and at last concatenated into a single feature vectors and generate D-LBP image. This feature are used for the representation of the face and to measure similarities between images. Keywords: local binary pattern (LBP), double coding local binary pattern (D-LBP), features extraction, classification, pattern recognition, histogram, feature vector.
Illumination Invariant Face Recognition System using Local Directional Patter...
The document proposes an illumination-robust face recognition system using local directional pattern (LDP) images and two-dimensional principal component analysis (2D-PCA). It extracts LDP images from face images as inputs to 2D-PCA for feature extraction, instead of using LDP for histogram feature extraction like previous works. Experimental results on the Yale B and CMU-PIE databases show the proposed approach achieves higher recognition accuracy than PCA and LBP-based methods, demonstrating its effectiveness in handling illumination variations. The maximum recognition rates are 96.43% for Yale B and 100% for CMU-PIE illumination sets.
Performance Evaluation of Illumination Invariant Face Recognition Algorthims
This document presents a performance evaluation of illumination invariant face recognition algorithms. It proposes a hybrid approach using Local Binary Pattern and Local Ternary Pattern fusion with gradient-based illumination normalization. The performance is evaluated using Receiver Operating Characteristics (ROC) curves and the proposed algorithm is shown to outperform traditional algorithms like Gradientfaces and Weberface on benchmark databases by achieving a higher true positive rate and lower false positive rate.
IRJET- Analysis of Face Recognition using Docface+ Selfie Matching
1. The document proposes a method called DocFace+ to automatically match ID document photos to selfie images in real-time with high accuracy.
2. It uses transfer learning by fine-tuning a base model trained on unconstrained face images on a private ID-selfie dataset. A pair of sibling networks are used to learn unified face representations.
3. Experimental results on an ID-selfie dataset show the proposed DocFace+ system achieves better generalization performance than publicly available general face matchers.
tScene classification using pyramid histogram of
This document proposes a new method called Pyramid Histogram of Multi-scale Block Local Binary Pattern (PH-MBLBP) for scene classification. PH-MBLBP encodes both micro- and macro-structures of image patterns to provide a more complete representation than basic LBP. It divides images into spatial regions at multiple resolutions to capture geometric information. Experiments on 15 scene categories show PH-MBLBP outperforms SIFT and provides a powerful yet fast texture descriptor for scene recognition.
Modified CSLBP
Image hashing is an efficient way to handle digital data authentication problem. Image hashing represents quality summarization of image features in compact manner. In this paper, the modified center symmetric local binary pattern (CSLBP) image hashing algorithm is proposed. Unlike CSLBP 16 bin histogram, Modified CSLBP generates 8 bin histogram without compromise on quality to generate compact hash. It has been found that, uniform quantization on a histogram with more bin results in more precision loss. To overcome quantization loss, modified CSLBP generates the two histogram of a four bin. Uniform quantization on a 4 bin histogram results in less precision loss than a 16 bin histogram. The first generated histogram represents the nearest neighbours and second one is for the diagonal neighbours. To enhance quality in terms of discrimination power, different weight factor are used during histogram generation. For the nearest and the diagonal neighbours, two local weight factors are used. One is the Standard Deviation (SD) and other is the Laplacian of Gaussian (LoG). Standard deviation represents a spread of data which captures local variation from mean. LoG is a second order derivative edge detection operator which detects edges well in presence of noise. The proposed algorithm is resilient to the various kinds of attacks. The proposed method is tested on database having malicious and non-malicious images using benchmark like NHD and ROC which confirms theoretical analysis. The experimental results shows good performance of the proposed method for various attacks despite the short hash length.
Dynamic Error Concealment Algorithm for Multiview Coding Using Lost MBs Size...
The document proposes an adaptive error concealment algorithm for multiview video coding that exploits spatial, temporal, and inter-view information. For intra macroblocks, a Spatial-Inter View algorithm is used to conceal errors using weighted pixel averaging and disparity vectors from other views. For inter macroblocks, the algorithm adaptively selects candidate macroblocks for replacement based on the size of the lost macroblock and the view of the reference frame, generating additional candidates to find better matches. Simulation results show the proposed algorithm achieves up to 12.4 dB and 0.73 dB higher PSNR than applying no error concealment or a normal algorithm, respectively, with better subjective quality and lower complexity.
A survey on feature descriptors for texture image classification
This document discusses various feature descriptors that can be used for texture image classification. It provides an overview of 8 different feature descriptors that have been proposed in recent research: local binary patterns (LBP), dominant local binary patterns (DLBP), completed local binary patterns (CLBP), Weber local descriptor (WLD), local binary count (LBC), discriminant face descriptor (DFD), local vector quantization pattern (LVQP), and dense micro-block difference (DMD). For each descriptor, it briefly explains the approach and compares the methods. The goal of the descriptors is to effectively capture textural features while addressing challenges like rotation, illumination changes, and noise.
Local directional number pattern for face analysis face and expression recogn...
Local directional number pattern for face analysis face and expression recogn...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.orgGABOR WAVELETS AND MORPHOLOGICAL SHARED WEIGHTED NEURAL NETWORK BASED AUTOMAT...
1) The document proposes an automatic face recognition system using Gabor wavelet face detection with neural networks and morphological shared weighted neural networks (MSNN) for face recognition.
2) Face detection is performed using Gabor filters for feature extraction and a neural network for classification. Detected faces are input to the MSNN for face recognition.
3) The MSNN uses hit-miss transforms for feature extraction in each layer, which are independent of grayscale shifts. Feature matching compares output thresholds to identify faces.
REAL-TIME SCENE TEXT LOCALIZATION AND RECOGNITION ppt.pptx
The document summarizes a student project on real-time scene text localization and recognition. It includes an introduction describing the challenges of natural scene text detection compared to well-formatted documents. It also describes previous work on text localization and recognition methods, the proposed image processing and MATLAB software used in the project, experimental results and analysis, and conclusions. The project aims to develop a new video scene text detection method using image enhancement and a Bayesian classifier to classify text pixels without prior image knowledge.
Matlab abstract 2016
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Review On Different Feature Extraction Algorithms
This document discusses different feature extraction algorithms that can be used in visual sensor networks (WVSN). It begins by explaining the traditional "compress-then-analyze" approach and introduces the newer "analyze-then-compress" approach. The document then reviews several real-valued and binary feature extraction algorithms such as SIFT, SURF, BRIEF, BRISK, and BinBoost. It proposes a video coding system that uses the BRISK algorithm to extract features, encodes the features using entropy coding, and transmits the data to a base station for matching with stored image data. Diagrams of the proposed system and the BRISK algorithm are also included.
Side-Match Vector Quantizers Using Neural Network Based Variance Predictor fo...
Side-match vector quantizer reduces bit-rates in image coding by using smaller-sized state codebooks generated from a master codebook through exploiting the correlations of neighboring vectors. This paper presents a new neural network based side-match vector quantization method for image coding. In this method, based on the variance of a vector which is predicted by a neural network, a subset of the codewords in the master codebook is selected for the side-matching to construct the state codebook for the encoding of the vector. This technique generates a lower encoding bit rate with a higher reconstructed image quality. Experimental results demonstrate that in terms of PSNR (Peak Signal-to-Noise Ratio) of the reconstructed images, the proposed method significantly outperforms the regular side-match vector quantizer, especially at lower coding bit-rates.
IRJET- Digital Image Forgery Detection using Local Binary Patterns (LBP) and ...
This document proposes a method to detect digital image forgeries using local binary patterns (LBP) and histogram of oriented gradients (HOG). It extracts LBP features from the input image, then applies HOG to the LBP features. These combined features are classified using a support vector machine (SVM) as authentic or tampered. Testing on CASIA datasets achieved detection rates of 92.3% for CASIA-1 and 96.1% for CASIA-2, outperforming other existing methods. The method is effective at forgery detection while having reduced time complexity.
MSB based Face Recognition Using Compression and Dual Matching Techniques
Biometrics are used in almost all communication technology applications for secure recognition. In this paper, we propose MSB based face recognition using compression and dual matching techniques. The standard available face images are considered to test the proposed method. The novel concept of considering only four Most Significant Bits (MSB) of each pixel on image is introduced to reduce the total number of bits to half of an image for high speed computation and less architectural complexity. The Discrete Wavelet Transform (DWT) is applied to an image with only MSB's, and consider only LL band coefficients as final features. The features of the database and test images are compared using Euclidian Distance (ED) an Artificial Neural Network (ANN) to test the performance of the pot method. It is observed that, the performance of the proposed method is better than the existing methods.
EFFICIENT STEREO VIDEO ENCODING FOR MOBILE APPLICATIONS USING THE 3D+F CODEC
Paper presented at the 3DTV-CON, Zurich, 15-17.10.2012
https://sites.google.com/a/disneyresearch.com/3dtv-con2012/
Matching Sketches with Digital Face Images using MCWLD and Image Moment Invar...
Face recognition is an important problem in many application domains. Matching sketches with
digital face image is important in solving crimes and capturing criminals. It is a computer application for
automatically identifying a person from a still image. Law enforcement agencies are progressively using
composite sketches and forensic sketches for catching the criminals. This paper presents two algorithms that
efficiently retrieve the matched results. First method uses multiscale circular Weber’s local descriptor to encode
more discriminative local micro patterns from local regions. Second method uses image moments, it extracts
discriminative shape, orientation, and texture features from local regions of a face. The discriminating
information from both sketch and digital image is compared using appropriate distance measure. The
contributions of this research paper are: i) Comparison of multiscale circular Weber’s local descriptor with
image moment for matching sketch to digital image, ii) Analysis of these algorithms on viewed face sketch,
forensic face sketch and composite face sketch databases
S01761131137
This document presents two algorithms for matching sketches to digital face images: 1) Multiscale Circular Weber's Local Descriptor (MCWLD) and 2) Image Moment Invariant. MCWLD encodes discriminative local micro patterns from local regions at multiple scales in a circular manner. Image Moment Invariant extracts shape, orientation, and texture features from local regions using image moments. Both extract distinguishing information from sketches and images, which are then compared using distance measures to find matches. The paper analyzes the performance of these algorithms on viewed, forensic, and composite sketch databases.
Local directional number pattern for face analysis face and expression recogn...
Final Year IEEE Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE Projects, Academic Final Year IEEE Projects 2013, Academic Final Year IEEE Projects 2014, IEEE MATLAB Projects, 2013 IEEE MATLAB Projects, 2013 IEEE MATLAB Projects in Chennai, 2013 IEEE MATLAB Projects in Trichy, 2013 IEEE MATLAB Projects in Karur, 2013 IEEE MATLAB Projects in Erode, 2013 IEEE MATLAB Projects in Madurai, 2013 IEEE MATLAB Projects in Salem, 2013 IEEE MATLAB Projects in Coimbatore, 2013 IEEE MATLAB Projects in Tirupur, 2013 IEEE MATLAB Projects in Bangalore, 2013 IEEE MATLAB Projects in Hydrabad, 2013 IEEE MATLAB Projects in Kerala, 2013 IEEE MATLAB Projects in Namakkal, IEEE MATLAB Image Processing, IEEE MATLAB Face Recognition, IEEE MATLAB Face Detection, IEEE MATLAB Brain Tumour, IEEE MATLAB Iris Recognition, IEEE MATLAB Image Segmentation, Final Year Matlab Projects in Pondichery, Final Year Matlab Projects in Tamilnadu, Final Year Matlab Projects in Chennai, Final Year Matlab Projects in Trichy, Final Year Matlab Projects in Erode, Final Year Matlab Projects in Karur, Final Year Matlab Projects in Coimbatore, Final Year Matlab Projects in Tirunelveli, Final Year Matlab Projects in Madurai, Final Year Matlab Projects in Salem, Final Year Matlab Projects in Tirupur, Final Year Matlab Projects in Namakkal, Final Year Matlab Projects in Tanjore, Final Year Matlab Projects in Coimbatore, Final Year Matlab Projects in Bangalore, Final Year Matlab Projects in Hydrabad, Final Year Matlab Projects in Kerala.
Matlab local directional number pattern for face analysis face and expressio...
Final Year IEEE Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE Projects, Academic Final Year IEEE Projects 2013, Academic Final Year IEEE Projects 2014, IEEE MATLAB Projects, 2013 IEEE MATLAB Projects, 2013 IEEE MATLAB Projects in Chennai, 2013 IEEE MATLAB Projects in Trichy, 2013 IEEE MATLAB Projects in Karur, 2013 IEEE MATLAB Projects in Erode, 2013 IEEE MATLAB Projects in Madurai, 2013 IEEE MATLAB Projects in Salem, 2013 IEEE MATLAB Projects in Coimbatore, 2013 IEEE MATLAB Projects in Tirupur, 2013 IEEE MATLAB Projects in Bangalore, 2013 IEEE MATLAB Projects in Hydrabad, 2013 IEEE MATLAB Projects in Kerala, 2013 IEEE MATLAB Projects in Namakkal, IEEE MATLAB Image Processing, IEEE MATLAB Face Recognition, IEEE MATLAB Face Detection, IEEE MATLAB Brain Tumour, IEEE MATLAB Iris Recognition, IEEE MATLAB Image Segmentation, Final Year Matlab Projects in Pondichery, Final Year Matlab Projects in Tamilnadu, Final Year Matlab Projects in Chennai, Final Year Matlab Projects in Trichy, Final Year Matlab Projects in Erode, Final Year Matlab Projects in Karur, Final Year Matlab Projects in Coimbatore, Final Year Matlab Projects in Tirunelveli, Final Year Matlab Projects in Madurai, Final Year Matlab Projects in Salem, Final Year Matlab Projects in Tirupur, Final Year Matlab Projects in Namakkal, Final Year Matlab Projects in Tanjore, Final Year Matlab Projects in Coimbatore, Final Year Matlab Projects in Bangalore, Final Year Matlab Projects in Hydrabad, Final Year Matlab Projects in Kerala.
ANALYSING JPEG CODING WITH MASKING
The growing trend of online image sharing and downloads today mandate the need for better encoding and
decoding scheme. This paper looks into this issue of image coding. Multiple Description Coding is an
encoding and decoding scheme that is specially designed in providing more error resilience for data
transmission. The main issue of Multiple Description Coding is the lossy transmission channels. This work
attempts to address the issue of re-constructing high quality image with the use of just one descriptor
rather than the conventional descriptor. This work compare the use of Type I quantizer and Type II
quantizer. We propose and compare 4 coders by examining the quality of re-constructed images. The 4
coders are namely JPEG HH (Horizontal Pixel Interleaving with Huffman Coding) model, JPEG HA
(Horizontal Pixel Interleaving with Arithmetic Encoding) model, JPEG VH (Vertical Pixel Interleaving
with Huffman Encoding) model, and JPEG VA (Vertical Pixel Interleaving with Arithmetic Encoding)
model. The findings suggest that the use of horizontal and vertical pixel interleavings do not affect the
results much. Whereas the choice of quantizer greatly affect its performance.
Hybrid Domain based Face Recognition using DWT, FFT and Compressed CLBP
The characteristics of human body parts and behaviour are measured with biometrics, which are used to authenticate a person. In this paper, we propose Hybrid Domain based Face Recognition using DWT, FFT and Compressed CLBP. The face images are preprocessed to enhance sharpness of images using Discrete Wavelet Transform (DWT) and Laplacian filter. The Compound Local Binary Pattern (CLBP) is applied on sharpened preprocessed face image to compute magnitude and sign components. The histogram is applied on CLBP components to compress number of features. The Fast Fourier Transformation (FFT) is applied on preprocessed image and compute magnitudes. The histogram features and FFT magnitude features are fused to generate final feature. The Euclidian Distance (ED) is used to compare final features of test face images with data base face images to compute performance parameters. It is observed that the percentage recognition rate is high in the case of proposed algorithm compared to existing algorithms.
IRJET- A Review on Face Recognition using Local Binary Pattern Algorithm
This document summarizes research on face recognition using the Local Binary Pattern (LBP) algorithm. It begins with an abstract describing biometric identification and how face recognition has become popular in computer vision applications. It then provides details on LBP, describing it as a visual descriptor used for classification. The document reviews how LBP extracts texture features from faces for recognition purposes. It outlines the face recognition process, including detection, feature extraction using LBP, and matching features to a gallery for identification.
IRJET-Face Recognition using LDN Code
J.K.Jeevitha ,B.Karthika,E.Devipriya "Face Recognition using LDN Code", International Research Journal of Engineering and Technology (IRJET), Volume2,issue-01 April 2015.e-ISSN:2395-0056, p-ISSN:2395-0072. www.irjet.net
Abstract
LDN characterizes both the texture and contrast information of facial components in a compact way, producing a more discriminative code than other available methods. An LDN code is obtained by computing the edge response values in 8 directions at each pixel with the aid of a compass mask. Image analysis and understanding has recently received significant attention, especially during the past several years. At least two reasons can be accounted for this trend: the first is the wide range of commercial and law enforcement applications, and the second is the availability of feasible technologies after nearly 30 years of research. In this paper we propose a novel local feature descriptor, called Local Directional Number Pattern (LDN), for face analysis, i.e., face and expression recognition. LDN characterizes both the texture and contrast information of facial components in a compact way, producing a more discriminative code than other available methods.
IRJET- Two Layer QR Code with Picture Embedding
This document presents a method for creating two-layer QR codes that can display two different messages or patterns when viewed from different directions. Specifically:
- A two-layer QR code structure is proposed, with a top transparent layer and bottom black/white layer, allowing two independent QR codes to be seen separately depending on viewing angle.
- An algorithm is described for generating these two-layer QR codes by optimizing the module patterns to best match target QR codes for the two messages while maximizing error correction.
- The technique is said to be useful for displaying multiple messages or translations in situations like stores with multiple payment options or apps with different download links by platform.
- Additionally, the document discusses embedding
Facial expression recognition on real world face images (OPTIK)
The following presentation is the summarized form of a research paper named as "Facial expression recognition on real world face images ( OPTIK ) ".
Add
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Design of a low voltage low-dropout regulator
This document outlines the sections and contents for a project report on designing a low-voltage low-dropout regulator. It includes sections for an abstract, introduction, literature survey, existing and proposed systems, advantages, requirements, diagrams, implementation, testing, conclusions, and references. Contact information and course offerings are also provided for i3e Technologies.
More Related Content
Similar to LEARNING COMPACT BINARY FACE DESCRIPTOR FOR FACE RECOGNITION
A survey on feature descriptors for texture image classification
This document discusses various feature descriptors that can be used for texture image classification. It provides an overview of 8 different feature descriptors that have been proposed in recent research: local binary patterns (LBP), dominant local binary patterns (DLBP), completed local binary patterns (CLBP), Weber local descriptor (WLD), local binary count (LBC), discriminant face descriptor (DFD), local vector quantization pattern (LVQP), and dense micro-block difference (DMD). For each descriptor, it briefly explains the approach and compares the methods. The goal of the descriptors is to effectively capture textural features while addressing challenges like rotation, illumination changes, and noise.
Local directional number pattern for face analysis face and expression recogn...
Local directional number pattern for face analysis face and expression recogn...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.orgGABOR WAVELETS AND MORPHOLOGICAL SHARED WEIGHTED NEURAL NETWORK BASED AUTOMAT...
1) The document proposes an automatic face recognition system using Gabor wavelet face detection with neural networks and morphological shared weighted neural networks (MSNN) for face recognition.
2) Face detection is performed using Gabor filters for feature extraction and a neural network for classification. Detected faces are input to the MSNN for face recognition.
3) The MSNN uses hit-miss transforms for feature extraction in each layer, which are independent of grayscale shifts. Feature matching compares output thresholds to identify faces.
REAL-TIME SCENE TEXT LOCALIZATION AND RECOGNITION ppt.pptx
The document summarizes a student project on real-time scene text localization and recognition. It includes an introduction describing the challenges of natural scene text detection compared to well-formatted documents. It also describes previous work on text localization and recognition methods, the proposed image processing and MATLAB software used in the project, experimental results and analysis, and conclusions. The project aims to develop a new video scene text detection method using image enhancement and a Bayesian classifier to classify text pixels without prior image knowledge.
Matlab abstract 2016
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Review On Different Feature Extraction Algorithms
This document discusses different feature extraction algorithms that can be used in visual sensor networks (WVSN). It begins by explaining the traditional "compress-then-analyze" approach and introduces the newer "analyze-then-compress" approach. The document then reviews several real-valued and binary feature extraction algorithms such as SIFT, SURF, BRIEF, BRISK, and BinBoost. It proposes a video coding system that uses the BRISK algorithm to extract features, encodes the features using entropy coding, and transmits the data to a base station for matching with stored image data. Diagrams of the proposed system and the BRISK algorithm are also included.
Side-Match Vector Quantizers Using Neural Network Based Variance Predictor fo...
Side-match vector quantizer reduces bit-rates in image coding by using smaller-sized state codebooks generated from a master codebook through exploiting the correlations of neighboring vectors. This paper presents a new neural network based side-match vector quantization method for image coding. In this method, based on the variance of a vector which is predicted by a neural network, a subset of the codewords in the master codebook is selected for the side-matching to construct the state codebook for the encoding of the vector. This technique generates a lower encoding bit rate with a higher reconstructed image quality. Experimental results demonstrate that in terms of PSNR (Peak Signal-to-Noise Ratio) of the reconstructed images, the proposed method significantly outperforms the regular side-match vector quantizer, especially at lower coding bit-rates.
IRJET- Digital Image Forgery Detection using Local Binary Patterns (LBP) and ...
This document proposes a method to detect digital image forgeries using local binary patterns (LBP) and histogram of oriented gradients (HOG). It extracts LBP features from the input image, then applies HOG to the LBP features. These combined features are classified using a support vector machine (SVM) as authentic or tampered. Testing on CASIA datasets achieved detection rates of 92.3% for CASIA-1 and 96.1% for CASIA-2, outperforming other existing methods. The method is effective at forgery detection while having reduced time complexity.
MSB based Face Recognition Using Compression and Dual Matching Techniques
Biometrics are used in almost all communication technology applications for secure recognition. In this paper, we propose MSB based face recognition using compression and dual matching techniques. The standard available face images are considered to test the proposed method. The novel concept of considering only four Most Significant Bits (MSB) of each pixel on image is introduced to reduce the total number of bits to half of an image for high speed computation and less architectural complexity. The Discrete Wavelet Transform (DWT) is applied to an image with only MSB's, and consider only LL band coefficients as final features. The features of the database and test images are compared using Euclidian Distance (ED) an Artificial Neural Network (ANN) to test the performance of the pot method. It is observed that, the performance of the proposed method is better than the existing methods.
EFFICIENT STEREO VIDEO ENCODING FOR MOBILE APPLICATIONS USING THE 3D+F CODEC
Paper presented at the 3DTV-CON, Zurich, 15-17.10.2012
https://sites.google.com/a/disneyresearch.com/3dtv-con2012/
Matching Sketches with Digital Face Images using MCWLD and Image Moment Invar...
Face recognition is an important problem in many application domains. Matching sketches with
digital face image is important in solving crimes and capturing criminals. It is a computer application for
automatically identifying a person from a still image. Law enforcement agencies are progressively using
composite sketches and forensic sketches for catching the criminals. This paper presents two algorithms that
efficiently retrieve the matched results. First method uses multiscale circular Weber’s local descriptor to encode
more discriminative local micro patterns from local regions. Second method uses image moments, it extracts
discriminative shape, orientation, and texture features from local regions of a face. The discriminating
information from both sketch and digital image is compared using appropriate distance measure. The
contributions of this research paper are: i) Comparison of multiscale circular Weber’s local descriptor with
image moment for matching sketch to digital image, ii) Analysis of these algorithms on viewed face sketch,
forensic face sketch and composite face sketch databases
S01761131137
This document presents two algorithms for matching sketches to digital face images: 1) Multiscale Circular Weber's Local Descriptor (MCWLD) and 2) Image Moment Invariant. MCWLD encodes discriminative local micro patterns from local regions at multiple scales in a circular manner. Image Moment Invariant extracts shape, orientation, and texture features from local regions using image moments. Both extract distinguishing information from sketches and images, which are then compared using distance measures to find matches. The paper analyzes the performance of these algorithms on viewed, forensic, and composite sketch databases.
Local directional number pattern for face analysis face and expression recogn...
Final Year IEEE Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE Projects, Academic Final Year IEEE Projects 2013, Academic Final Year IEEE Projects 2014, IEEE MATLAB Projects, 2013 IEEE MATLAB Projects, 2013 IEEE MATLAB Projects in Chennai, 2013 IEEE MATLAB Projects in Trichy, 2013 IEEE MATLAB Projects in Karur, 2013 IEEE MATLAB Projects in Erode, 2013 IEEE MATLAB Projects in Madurai, 2013 IEEE MATLAB Projects in Salem, 2013 IEEE MATLAB Projects in Coimbatore, 2013 IEEE MATLAB Projects in Tirupur, 2013 IEEE MATLAB Projects in Bangalore, 2013 IEEE MATLAB Projects in Hydrabad, 2013 IEEE MATLAB Projects in Kerala, 2013 IEEE MATLAB Projects in Namakkal, IEEE MATLAB Image Processing, IEEE MATLAB Face Recognition, IEEE MATLAB Face Detection, IEEE MATLAB Brain Tumour, IEEE MATLAB Iris Recognition, IEEE MATLAB Image Segmentation, Final Year Matlab Projects in Pondichery, Final Year Matlab Projects in Tamilnadu, Final Year Matlab Projects in Chennai, Final Year Matlab Projects in Trichy, Final Year Matlab Projects in Erode, Final Year Matlab Projects in Karur, Final Year Matlab Projects in Coimbatore, Final Year Matlab Projects in Tirunelveli, Final Year Matlab Projects in Madurai, Final Year Matlab Projects in Salem, Final Year Matlab Projects in Tirupur, Final Year Matlab Projects in Namakkal, Final Year Matlab Projects in Tanjore, Final Year Matlab Projects in Coimbatore, Final Year Matlab Projects in Bangalore, Final Year Matlab Projects in Hydrabad, Final Year Matlab Projects in Kerala.
Matlab local directional number pattern for face analysis face and expressio...
Final Year IEEE Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE Projects, Academic Final Year IEEE Projects 2013, Academic Final Year IEEE Projects 2014, IEEE MATLAB Projects, 2013 IEEE MATLAB Projects, 2013 IEEE MATLAB Projects in Chennai, 2013 IEEE MATLAB Projects in Trichy, 2013 IEEE MATLAB Projects in Karur, 2013 IEEE MATLAB Projects in Erode, 2013 IEEE MATLAB Projects in Madurai, 2013 IEEE MATLAB Projects in Salem, 2013 IEEE MATLAB Projects in Coimbatore, 2013 IEEE MATLAB Projects in Tirupur, 2013 IEEE MATLAB Projects in Bangalore, 2013 IEEE MATLAB Projects in Hydrabad, 2013 IEEE MATLAB Projects in Kerala, 2013 IEEE MATLAB Projects in Namakkal, IEEE MATLAB Image Processing, IEEE MATLAB Face Recognition, IEEE MATLAB Face Detection, IEEE MATLAB Brain Tumour, IEEE MATLAB Iris Recognition, IEEE MATLAB Image Segmentation, Final Year Matlab Projects in Pondichery, Final Year Matlab Projects in Tamilnadu, Final Year Matlab Projects in Chennai, Final Year Matlab Projects in Trichy, Final Year Matlab Projects in Erode, Final Year Matlab Projects in Karur, Final Year Matlab Projects in Coimbatore, Final Year Matlab Projects in Tirunelveli, Final Year Matlab Projects in Madurai, Final Year Matlab Projects in Salem, Final Year Matlab Projects in Tirupur, Final Year Matlab Projects in Namakkal, Final Year Matlab Projects in Tanjore, Final Year Matlab Projects in Coimbatore, Final Year Matlab Projects in Bangalore, Final Year Matlab Projects in Hydrabad, Final Year Matlab Projects in Kerala.
ANALYSING JPEG CODING WITH MASKING
The growing trend of online image sharing and downloads today mandate the need for better encoding and
decoding scheme. This paper looks into this issue of image coding. Multiple Description Coding is an
encoding and decoding scheme that is specially designed in providing more error resilience for data
transmission. The main issue of Multiple Description Coding is the lossy transmission channels. This work
attempts to address the issue of re-constructing high quality image with the use of just one descriptor
rather than the conventional descriptor. This work compare the use of Type I quantizer and Type II
quantizer. We propose and compare 4 coders by examining the quality of re-constructed images. The 4
coders are namely JPEG HH (Horizontal Pixel Interleaving with Huffman Coding) model, JPEG HA
(Horizontal Pixel Interleaving with Arithmetic Encoding) model, JPEG VH (Vertical Pixel Interleaving
with Huffman Encoding) model, and JPEG VA (Vertical Pixel Interleaving with Arithmetic Encoding)
model. The findings suggest that the use of horizontal and vertical pixel interleavings do not affect the
results much. Whereas the choice of quantizer greatly affect its performance.
Hybrid Domain based Face Recognition using DWT, FFT and Compressed CLBP
The characteristics of human body parts and behaviour are measured with biometrics, which are used to authenticate a person. In this paper, we propose Hybrid Domain based Face Recognition using DWT, FFT and Compressed CLBP. The face images are preprocessed to enhance sharpness of images using Discrete Wavelet Transform (DWT) and Laplacian filter. The Compound Local Binary Pattern (CLBP) is applied on sharpened preprocessed face image to compute magnitude and sign components. The histogram is applied on CLBP components to compress number of features. The Fast Fourier Transformation (FFT) is applied on preprocessed image and compute magnitudes. The histogram features and FFT magnitude features are fused to generate final feature. The Euclidian Distance (ED) is used to compare final features of test face images with data base face images to compute performance parameters. It is observed that the percentage recognition rate is high in the case of proposed algorithm compared to existing algorithms.
IRJET- A Review on Face Recognition using Local Binary Pattern Algorithm
This document summarizes research on face recognition using the Local Binary Pattern (LBP) algorithm. It begins with an abstract describing biometric identification and how face recognition has become popular in computer vision applications. It then provides details on LBP, describing it as a visual descriptor used for classification. The document reviews how LBP extracts texture features from faces for recognition purposes. It outlines the face recognition process, including detection, feature extraction using LBP, and matching features to a gallery for identification.
IRJET-Face Recognition using LDN Code
J.K.Jeevitha ,B.Karthika,E.Devipriya "Face Recognition using LDN Code", International Research Journal of Engineering and Technology (IRJET), Volume2,issue-01 April 2015.e-ISSN:2395-0056, p-ISSN:2395-0072. www.irjet.net
Abstract
LDN characterizes both the texture and contrast information of facial components in a compact way, producing a more discriminative code than other available methods. An LDN code is obtained by computing the edge response values in 8 directions at each pixel with the aid of a compass mask. Image analysis and understanding has recently received significant attention, especially during the past several years. At least two reasons can be accounted for this trend: the first is the wide range of commercial and law enforcement applications, and the second is the availability of feasible technologies after nearly 30 years of research. In this paper we propose a novel local feature descriptor, called Local Directional Number Pattern (LDN), for face analysis, i.e., face and expression recognition. LDN characterizes both the texture and contrast information of facial components in a compact way, producing a more discriminative code than other available methods.
IRJET- Two Layer QR Code with Picture Embedding
This document presents a method for creating two-layer QR codes that can display two different messages or patterns when viewed from different directions. Specifically:
- A two-layer QR code structure is proposed, with a top transparent layer and bottom black/white layer, allowing two independent QR codes to be seen separately depending on viewing angle.
- An algorithm is described for generating these two-layer QR codes by optimizing the module patterns to best match target QR codes for the two messages while maximizing error correction.
- The technique is said to be useful for displaying multiple messages or translations in situations like stores with multiple payment options or apps with different download links by platform.
- Additionally, the document discusses embedding
Facial expression recognition on real world face images (OPTIK)
The following presentation is the summarized form of a research paper named as "Facial expression recognition on real world face images ( OPTIK ) ".
Similar to LEARNING COMPACT BINARY FACE DESCRIPTOR FOR FACE RECOGNITION (20)
A survey on feature descriptors for texture image classification
A survey on feature descriptors for texture image classification
Local directional number pattern for face analysis face and expression recogn...
Local directional number pattern for face analysis face and expression recogn...
GABOR WAVELETS AND MORPHOLOGICAL SHARED WEIGHTED NEURAL NETWORK BASED AUTOMAT...
GABOR WAVELETS AND MORPHOLOGICAL SHARED WEIGHTED NEURAL NETWORK BASED AUTOMAT...
REAL-TIME SCENE TEXT LOCALIZATION AND RECOGNITION ppt.pptx
REAL-TIME SCENE TEXT LOCALIZATION AND RECOGNITION ppt.pptx
Side-Match Vector Quantizers Using Neural Network Based Variance Predictor fo...
Side-Match Vector Quantizers Using Neural Network Based Variance Predictor fo...
IRJET- Digital Image Forgery Detection using Local Binary Patterns (LBP) and ...
IRJET- Digital Image Forgery Detection using Local Binary Patterns (LBP) and ...
MSB based Face Recognition Using Compression and Dual Matching Techniques
MSB based Face Recognition Using Compression and Dual Matching Techniques
EFFICIENT STEREO VIDEO ENCODING FOR MOBILE APPLICATIONS USING THE 3D+F CODEC
EFFICIENT STEREO VIDEO ENCODING FOR MOBILE APPLICATIONS USING THE 3D+F CODEC
Matching Sketches with Digital Face Images using MCWLD and Image Moment Invar...
Matching Sketches with Digital Face Images using MCWLD and Image Moment Invar...
Local directional number pattern for face analysis face and expression recogn...
Local directional number pattern for face analysis face and expression recogn...
Matlab local directional number pattern for face analysis face and expressio...
Matlab local directional number pattern for face analysis face and expressio...
Hybrid Domain based Face Recognition using DWT, FFT and Compressed CLBP
Hybrid Domain based Face Recognition using DWT, FFT and Compressed CLBP
IRJET- A Review on Face Recognition using Local Binary Pattern Algorithm
IRJET- A Review on Face Recognition using Local Binary Pattern Algorithm
Facial expression recognition on real world face images (OPTIK)
Facial expression recognition on real world face images (OPTIK)
More from I3E Technologies
Add
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Design of a low voltage low-dropout regulator
This document outlines the sections and contents for a project report on designing a low-voltage low-dropout regulator. It includes sections for an abstract, introduction, literature survey, existing and proposed systems, advantages, requirements, diagrams, implementation, testing, conclusions, and references. Contact information and course offerings are also provided for i3e Technologies.
An efficient constant multiplier architecture based on vertical horizontal bi...
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Aging aware reliable multiplier design with adaptive hold logic
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
A high performance fir filter architecture for fixed and reconfigurable appli...
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
A generalized algorithm and reconfigurable architecture for efficient and sca...
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
A combined sdc sdf architecture for normal i o pipelined radix-2 fft
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Reverse converter design via parallel prefix adders novel components, method...
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Pre encoded multipliers based on non-redundant radix-4 signed-digit encoding
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Energy optimized subthreshold vlsi logic family with unbalanced pull up down ...
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Variable form carrier-based pwm for boost-voltage motor driver with a charge-...
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Ultrasparse ac link converters
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Single inductor dual-output buck–boost power factor correction converter
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Ripple minimization through harmonic elimination in asymmetric interleaved mu...
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Resonance analysis and soft switching design of isolated boost converter with...
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Reliability evaluation of conventional and interleaved dc–dc boost converters
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Power factor corrected zeta converter based improved power quality switched m...
The document describes a proposed switched mode power supply (SMPS) system that uses a front-end power factor corrected Zeta converter to improve power quality. The front-end converter reduces 100-Hz ripple and improves power factor and voltage regulation. Simulation and testing of a laboratory prototype showed the proposed SMPS enhanced performance under varying input voltages and loading conditions, meeting international power quality standards.
Pfc cuk converter fed bldc motor drive
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
Optimized operation of current fed dual active bridge dc dc converter for pv ...
This document discusses optimized operation of a current-fed dual active bridge DC-DC converter for photovoltaic applications. It analyzes the operating principle and soft-switching conditions over a wide operating range with phase shift and duty cycle control. An optimized operating mode is proposed to achieve minimum RMS transformer current and extend the soft-switching region to reduce losses. Experimental results from a 5 kW hardware prototype verify the analysis. Contact and location information is also provided for an organization that develops IEEE software and hardware projects.
Online variable topology type photovoltaic grid-connected inverter
I3E Technologies,
#23/A, 2nd Floor SKS Complex,
Opp. Bus Stand, Karur-639 001.
IEEE PROJECTS AVAILABLE,
NON-IEEE PROJECTS AVAILABLE,
APPLICATION BASED PROJECTS AVAILABLE,
MINI-PROJECTS AVAILABLE.
Mobile : 99436 99916, 99436 99926, 99436 99936
Mail ID: i3eprojectskarur@gmail.com
Web: www.i3etechnologies.com, www.i3eprojects.com
More from I3E Technologies (20)
An efficient constant multiplier architecture based on vertical horizontal bi...
An efficient constant multiplier architecture based on vertical horizontal bi...
Aging aware reliable multiplier design with adaptive hold logic
Aging aware reliable multiplier design with adaptive hold logic
A high performance fir filter architecture for fixed and reconfigurable appli...
A high performance fir filter architecture for fixed and reconfigurable appli...
A generalized algorithm and reconfigurable architecture for efficient and sca...
A generalized algorithm and reconfigurable architecture for efficient and sca...
A combined sdc sdf architecture for normal i o pipelined radix-2 fft
A combined sdc sdf architecture for normal i o pipelined radix-2 fft
Reverse converter design via parallel prefix adders novel components, method...
Reverse converter design via parallel prefix adders novel components, method...
Pre encoded multipliers based on non-redundant radix-4 signed-digit encoding
Pre encoded multipliers based on non-redundant radix-4 signed-digit encoding
Energy optimized subthreshold vlsi logic family with unbalanced pull up down ...
Energy optimized subthreshold vlsi logic family with unbalanced pull up down ...
Variable form carrier-based pwm for boost-voltage motor driver with a charge-...
Variable form carrier-based pwm for boost-voltage motor driver with a charge-...
Single inductor dual-output buck–boost power factor correction converter
Single inductor dual-output buck–boost power factor correction converter
Ripple minimization through harmonic elimination in asymmetric interleaved mu...
Ripple minimization through harmonic elimination in asymmetric interleaved mu...
Resonance analysis and soft switching design of isolated boost converter with...
Resonance analysis and soft switching design of isolated boost converter with...
Reliability evaluation of conventional and interleaved dc–dc boost converters
Reliability evaluation of conventional and interleaved dc–dc boost converters
Power factor corrected zeta converter based improved power quality switched m...
Power factor corrected zeta converter based improved power quality switched m...
Optimized operation of current fed dual active bridge dc dc converter for pv ...
Optimized operation of current fed dual active bridge dc dc converter for pv ...
Online variable topology type photovoltaic grid-connected inverter
Online variable topology type photovoltaic grid-connected inverter
Recently uploaded
一比一原版(USF毕业证)旧金山大学毕业证如何办理
原件一模一样【微信：95270640】【旧金山大学毕业证USF学位证成绩单】【微信：95270640】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
【业务选择办理准则】
一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信：95270640】文凭即可
二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信：95270640】即可
三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。
留信网认证的作用:
1:该专业认证可证明留学生真实身份【微信：95270640】
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
→ 【关于价格问题（保证一手价格）
我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子 我给客户的都是第一手的代理价格，因为我想坦诚对待大家 不想跟大家在价格方面浪费时间
对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
选择实体注册公司办理，更放心，更安全！我们的承诺：可来公司面谈，可签订合同，会陪同客户一起到教育部认证窗口递交认证材料，客户在教育部官方认证查询网站查询到认证通过结果后付款，不成功不收费！
办理旧金山大学毕业证毕业证学位证USF学位证【微信：95270640 】外观非常精致，由特殊纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理旧金山大学毕业证USF学位证毕业证学位证【微信：95270640 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理旧金山大学毕业证毕业证学位证USF学位证【微信：95270640 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理旧金山大学毕业证毕业证学位证USF学位证【微信：95270640 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
3rd International Conference on Artificial Intelligence Advances (AIAD 2024)
3rd International Conference on Artificial Intelligence Advances (AIAD 2024) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the area advanced Artificial Intelligence. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the research area. Core areas of AI and advanced multi-disciplinary and its applications will be covered during the conferences.
Applications of artificial Intelligence in Mechanical Engineering.pdf
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
DESIGN AND MANUFACTURE OF CEILING BOARD USING SAWDUST AND WASTE CARTON MATERI...
The need for ecofriendly materials as building materials in this century cannot be overemphasized
一比一原版(psu学位证书)美国匹兹堡州立大学毕业证如何办理
原版一模一样【微信：741003700 】【(psu学位证书)美国匹兹堡州立大学毕业证成绩单】【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
办理(psu学位证书)美国匹兹堡州立大学毕业证【微信：741003700 】外观非常简单，由纸质材料制成，上面印有校徽、校名、毕业生姓名、专业等信息。
办理(psu学位证书)美国匹兹堡州立大学毕业证【微信：741003700 】格式相对统一，各专业都有相应的模板。通常包括以下部分：
校徽：象征着学校的荣誉和传承。
校名:学校英文全称
授予学位：本部分将注明获得的具体学位名称。
毕业生姓名：这是最重要的信息之一，标志着该证书是由特定人员获得的。
颁发日期：这是毕业正式生效的时间，也代表着毕业生学业的结束。
其他信息：根据不同的专业和学位，可能会有一些特定的信息或章节。
办理(psu学位证书)美国匹兹堡州立大学毕业证【微信：741003700 】价值很高，需要妥善保管。一般来说，应放置在安全、干燥、防潮的地方，避免长时间暴露在阳光下。如需使用，最好使用复印件而不是原件，以免丢失。
综上所述，办理(psu学位证书)美国匹兹堡州立大学毕业证【微信：741003700 】是证明身份和学历的高价值文件。外观简单庄重，格式统一，包括重要的个人信息和发布日期。对持有人来说，妥善保管是非常重要的。
This study Examines the Effectiveness of Talent Procurement through the Imple...
In the world with high technology and fast
forward mindset recruiters are walking/showing interest
towards E-Recruitment. Present most of the HRs of
many companies are choosing E-Recruitment as the best
choice for recruitment. E-Recruitment is being done
through many online platforms like Linkedin, Naukri,
Instagram , Facebook etc. Now with high technology E-
Recruitment has gone through next level by using
Artificial Intelligence too.
Key Words : Talent Management, Talent Acquisition , E-
Recruitment , Artificial Intelligence Introduction
Effectiveness of Talent Acquisition through E-
Recruitment in this topic we will discuss about 4important
and interlinked topics which are
Supermarket Management System Project Report.pdf
Supermarket management is a stand-alone J2EE using Eclipse Juno program.
This project contains all the necessary required information about maintaining
the supermarket billing system.
The core idea of this project to minimize the paper work and centralize the
data. Here all the communication is taken in secure manner. That is, in this
application the information will be stored in client itself. For further security the
data base is stored in the back-end oracle and so no intruders can access it.
AI + Data Community Tour - Build the Next Generation of Apps with the Einstei...
AI + Data Community Tour - Build the Next Generation of Apps with the Einstei...Paris Salesforce Developer Group
Build the Next Generation of Apps with the Einstein 1 Platform.
Rejoignez Philippe Ozil pour une session de workshops qui vous guidera à travers les détails de la plateforme Einstein 1, l'importance des données pour la création d'applications d'intelligence artificielle et les différents outils et technologies que Salesforce propose pour vous apporter tous les bénéfices de l'IA.FULL STACK PROGRAMMING - Both Front End and Back End
This ppt gives details about Full Stack Programming and its basics.
Digital Twins Computer Networking Paper Presentation.pptx
A Digital Twin in computer networking is a virtual representation of a physical network, used to simulate, analyze, and optimize network performance and reliability. It leverages real-time data to enhance network management, predict issues, and improve decision-making processes.
An In-Depth Exploration of Natural Language Processing: Evolution, Applicatio...
Natural language processing (NLP) has
recently garnered significant interest for the
computational representation and analysis of human
language. Its applications span multiple domains such
as machine translation, email spam detection,
information extraction, summarization, healthcare,
and question answering. This paper first delineates
four phases by examining various levels of NLP and
components of Natural Language Generation,
followed by a review of the history and progression of
NLP. Subsequently, we delve into the current state of
the art by presenting diverse NLP applications,
contemporary trends, and challenges. Finally, we
discuss some available datasets, models, and
evaluation metrics in NLP.
Impartiality as per ISO /IEC 17025:2017 Standard
This document provides basic guidelines for imparitallity requirement of ISO 17025. It defines in detial how it is met and wiudhwdih jdhsjdhwudjwkdbjwkdddddddddddkkkkkkkkkkkkkkkkkkkkkkkwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwioiiiiiiiiiiiii uwwwwwwwwwwwwwwwwhe wiqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq gbbbbbbbbbbbbb owdjjjjjjjjjjjjjjjjjjjj widhi owqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq uwdhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhhwqiiiiiiiiiiiiiiiiiiiiiiiiiiiiw0pooooojjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjjj whhhhhhhhhhh wheeeeeeee wihieiiiiii wihe
e qqqqqqqqqqeuwiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiqw dddddddddd cccccccccccccccv s w c r
cdf cb bicbsad ishd d qwkbdwiur e wetwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwwww w
dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddfffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffw
uuuuhhhhhhhhhhhhhhhhhhhhhhhhe qiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiiii iqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqq eeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeeee qqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqqccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc ccccccccccccccccccccccccccccccccccc bbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbbu uuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuuum
m
m mmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmmm m i
g i dijsd sjdnsjd ndjajsdnnsa adjdnawddddddddddddd uw
SELENIUM CONF -PALLAVI SHARMA - 2024.pdf
Begin your journey to contribute to Selenium - A Talk at the Selenium Conference 2024
Recently uploaded (20)
3rd International Conference on Artificial Intelligence Advances (AIAD 2024)
3rd International Conference on Artificial Intelligence Advances (AIAD 2024)
Applications of artificial Intelligence in Mechanical Engineering.pdf
Applications of artificial Intelligence in Mechanical Engineering.pdf
DESIGN AND MANUFACTURE OF CEILING BOARD USING SAWDUST AND WASTE CARTON MATERI...
DESIGN AND MANUFACTURE OF CEILING BOARD USING SAWDUST AND WASTE CARTON MATERI...
Northrop Grumman - Aerospace Structures Overvi.pdf
Northrop Grumman - Aerospace Structures Overvi.pdf
This study Examines the Effectiveness of Talent Procurement through the Imple...
This study Examines the Effectiveness of Talent Procurement through the Imple...
openshift technical overview - Flow of openshift containerisatoin
openshift technical overview - Flow of openshift containerisatoin
SENTIMENT ANALYSIS ON PPT AND Project template_.pptx
SENTIMENT ANALYSIS ON PPT AND Project template_.pptx
AI + Data Community Tour - Build the Next Generation of Apps with the Einstei...
AI + Data Community Tour - Build the Next Generation of Apps with the Einstei...
FULL STACK PROGRAMMING - Both Front End and Back End
FULL STACK PROGRAMMING - Both Front End and Back End
Digital Twins Computer Networking Paper Presentation.pptx
Digital Twins Computer Networking Paper Presentation.pptx
An In-Depth Exploration of Natural Language Processing: Evolution, Applicatio...
An In-Depth Exploration of Natural Language Processing: Evolution, Applicatio...
LEARNING COMPACT BINARY FACE DESCRIPTOR FOR FACE RECOGNITION
- 1. LEARNING COMPACT BINARY FACE DESCRIPTOR FOR FACE RECOGNITION ABSTRACT Binary feature descriptors such as local binary patterns (LBP) and its variations have been widely used in many face recognition systems due to their excellent robustness and strong discriminative power. However, most existing binary face descriptors are hand-crafted, which require strong prior knowledge to engineer them by hand. In this paper, we propose a compact binary face descriptor (CBFD) feature learning method for face representation and recognition. Given each face image, we first extract pixel difference vectors (PDVs) in local patches by computing the difference between each pixel and its neighboring pixels. Then, we learn a feature mapping to project these pixel difference vectors (PDVs) into low-dimensional binary vectors in an unsupervised manner, where 1) the variance of all binary codes in the training set is maximized, 2) the loss between the original real-valued codes and the learned binary codes is minimized, and 3) binary codes evenly distribute at each learned bin, so that the redundancy information in PDVs is removed and compact binary codes are obtained. Lastly, we cluster and pool these binary codes into a histogram feature as the final representation for each face image. Moreover, we propose a coupled CBFD (C-CBFD) method by reducing the modality gap of heterogeneous faces at the feature level to make our method applicable to heterogeneous face recognition. Ext