An optimized modified booth recoder for efficient design of the add multiply ...LogicMindtech Nologies
VLSI Projects for M. Tech, VLSI Projects in Vijayanagar, VLSI Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, VLSI IEEE projects in Bangalore, IEEE 2015 VLSI Projects, FPGA and Xilinx Projects, FPGA and Xilinx Projects in Bangalore, FPGA and Xilinx Projects in Vijayangar
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Image segmentation refers to partitioning a digital image into multiple regions or sets of pixels based on characteristics like color or texture. The goal is to simplify the image representation to make it easier to analyze. Some applications in medical imaging include locating tumors, measuring tissue volumes, and computer-guided surgery. Common segmentation techniques include thresholding, edge detection, region growing, and split-and-merge approaches.
Realtime pothole detection system using improved CNN Modelsnithinsai2992
The document summarizes work on a real-time pothole detection system using improved CNN models. It discusses using the YOLOv5 model for pothole detection and training YOLOv5m6, YOLOv5s6, and YOLOv5n6 models on a dataset, achieving mAP scores of 80.8%, 82.2%, and 82.5% respectively. It also proposes further improving the system through techniques like better image processing during nighttime and enhancing detection of distant objects.
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
final year ieee pojects in pondicherry,bulk ieee projects ,bulk 2015-16 i...nexgentech
This document provides information about 12 MATLAB projects from 2015 conducted by Nexgen Technology. It lists the project topics, abstracts describing what each project involved, and the year 2015 for each entry. The document also provides contact information for Nexgen Technology, including their website, address, email, phone number, and mobile numbers.
An optimized modified booth recoder for efficient design of the add multiply ...LogicMindtech Nologies
VLSI Projects for M. Tech, VLSI Projects in Vijayanagar, VLSI Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, VLSI IEEE projects in Bangalore, IEEE 2015 VLSI Projects, FPGA and Xilinx Projects, FPGA and Xilinx Projects in Bangalore, FPGA and Xilinx Projects in Vijayangar
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Image segmentation refers to partitioning a digital image into multiple regions or sets of pixels based on characteristics like color or texture. The goal is to simplify the image representation to make it easier to analyze. Some applications in medical imaging include locating tumors, measuring tissue volumes, and computer-guided surgery. Common segmentation techniques include thresholding, edge detection, region growing, and split-and-merge approaches.
Realtime pothole detection system using improved CNN Modelsnithinsai2992
The document summarizes work on a real-time pothole detection system using improved CNN models. It discusses using the YOLOv5 model for pothole detection and training YOLOv5m6, YOLOv5s6, and YOLOv5n6 models on a dataset, achieving mAP scores of 80.8%, 82.2%, and 82.5% respectively. It also proposes further improving the system through techniques like better image processing during nighttime and enhancing detection of distant objects.
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
final year ieee pojects in pondicherry,bulk ieee projects ,bulk 2015-16 i...nexgentech
This document provides information about 12 MATLAB projects from 2015 conducted by Nexgen Technology. It lists the project topics, abstracts describing what each project involved, and the year 2015 for each entry. The document also provides contact information for Nexgen Technology, including their website, address, email, phone number, and mobile numbers.
In this project, we consider the deep learning-based approaches to performing Neural Style Transfer (NST) on images. In particular, we intend to assess the Real-Time performance of this approach, since it has become a trending topic both in academia and in industrial applications.
For this purpose, after exploring the perceptual loss concept, which is used by the majority of models when performing NST, we conducted a review on a range of existing methods for this practical problem. We found that the feedforward based methods allow to achieve real time performance as opposed to the framework of iterative optimization proposed in the original Neural Style Transfer algorithm introduced by Gatys et al. Which is why we mainly focused on two feed-forward methods proposed in the literature: one that focuses on Single-Style transfer, TransformNet, and one that tackles the more generic problem of Multiple Style Transfer, MSG-Net.
This document summarizes a student project report on neural style transfer. The students tested existing feed-forward neural style transfer methods (TransformNet and MSG-Net) and compared their real-time performance and visual quality. They also experimented with combining multiple styles using the original optimization-based neural style transfer algorithm. The document provides background on neural style transfer techniques, discusses the methods tested, and outlines the project's methodology for evaluating and comparing the methods.
Ieee projects 2012 2013 - Digital Image ProcessingK Sundaresh Ka
ieee projects download, base paper for ieee projects, ieee projects list, ieee projects titles, ieee projects for cse, ieee projects on networking,ieee projects 2012, ieee projects 2013, final year project, computer science final year projects, final year projects for information technology, ieee final year projects, final year students projects, students projects in java, students projects download, students projects in java with source code, students projects architecture, free ieee papers
Medial Axis Transformation based Skeletonzation of Image Patterns using Image...IOSR Journals
1) The document discusses extracting the medial axis transform (MAT) of an image pattern using the Euclidean distance transform. The image is first converted to binary, then the Euclidean distance transform is used to compute the distance of each non-zero pixel to the closest zero pixel.
2) The medial axis transform represents the core or skeleton of an image pattern. There are different algorithms for extracting the skeleton or medial axis, including sequential and parallel algorithms. The skeleton provides a simple representation that preserves topological and size characteristics of the original shape.
3) The document provides background on medial axis transforms and different skeletonization algorithms. It then describes preparing the binary image and applying the Euclidean distance transform to extract the MAT and skeleton
An improved image compression algorithm based on daubechies wavelets with ar...Alexander Decker
This document summarizes an academic article that proposes a new image compression algorithm using Daubechies wavelets and arithmetic coding. It first discusses existing image compression techniques and their limitations. It then describes the proposed algorithm, which applies Daubechies wavelet transform followed by 2D Walsh wavelet transform on image blocks and arithmetic coding. Results show the proposed method achieves higher compression ratios and PSNR values than existing algorithms like EZW and SPIHT. Future work aims to improve results by exploring different wavelets and compression techniques.
This document provides information about Elysium Technologies Private Limited, an ISO 9001:2008 certified research and development company located in Singapore, Madurai, Trichy, Coimbatore, Kollam, and Cochin. It lists their branch office locations and contact information. The document then provides a list of 12 digital image processing projects available for the 2012-2013 academic year.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
An Intelligent approach to Pic to Cartoon Conversion using White-box-cartooni...IRJET Journal
This document presents an intelligent approach for converting photographs to cartoons. It proposes extracting three representations from images - the surface representation containing smooth surfaces, the structure representation containing thin color blocks and flattened surfaces, and the texture representation containing high-frequency textures and contours. A generative adversarial network is trained on these extracted representations to generate cartoonized images. The approach is implemented in a web application that allows users to upload images and obtain cartoonized outputs in a few seconds. Quantitative and qualitative evaluations demonstrate the approach outperforms previous methods.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
The document proposes a new framework called structure-modulated sparse representation (SMSR) for single image super-resolution. Existing super-resolution methods increase artifacts and do not consider image structure. The proposed SMSR algorithm formulates an optimization problem using gradient priors and nonlocal sparsity to reconstruct high-resolution images. It exploits multi-scale similarity using multi-step magnification and ridge regression for initial estimation. The algorithm also incorporates gradient histogram preservation as a regularization term. Experimental results show the proposed method outperforms state-of-the-art methods in recovering fine structures and details from low-resolution images.
This document discusses image compression using discrete wavelet transform (DWT) and principal component analysis (PCA). It first reviews several related works that use transforms like curvelet, wavelet and discrete cosine transform for image compression. It then describes preprocessing the input image using DWT to decompose it into sub-bands, and applying PCA on the high-frequency sub-bands to reduce dimensions and compress the image while preserving important boundaries. The algorithm is implemented and evaluated based on metrics like peak signal-to-noise ratio, standard deviation and entropy. Results show 95% accuracy in image identification from a database, though processing time increases significantly with database size.
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
IEEE Final Year Projects 2011-2012 :: Elysium Technologies Pvt Ltd::Imageproc...sunda2011
The document is a list of 13 image processing projects from 2011-2012 by Elysium Technologies Private Limited. It includes projects on 1D transforms for motion compensation residuals, edge preserving MAP estimation of images, a generalized unsharp masking algorithm, optimal design of color filter arrays, text detection in natural scenes, contrast-tone mapping, subspace optimization for image restoration, joint image registration and fusion, an easy path wavelet transform for image approximation, 3D color histogram equalization with uniform 1D grayscale histogram, camera calibration using spheres, estimating illumination chromaticity and correspondence, and variational histogram transfer of color images.
Orthogonal Matching Pursuit in 2D for Java with GPGPU ProspectivesMatt Simons
This document summarizes a project that implemented the Orthogonal Matching Pursuit algorithm in two dimensions (OMP2D) in Java and created an ImageJ plugin to apply it. It discusses the algorithm, details the Java implementation and optimizations, and proposes methods for accelerating it using GPUs. The author created a fully functional OMP2D ImageJ plugin with good performance compared to other implementations. The open source software and documentation are publicly available. The document outlines how further speed improvements could be achieved through mass parallelization on GPUs.
Image segmentation Based on Chan-Vese Active Contours using Finite Difference...ijsrd.com
There are a lot of image segmentation techniques that try to differentiate between backgrounds and object pixels but many of them fail to discriminate between different objects that are close to each other, e.g. low contrast between foreground and background regions increase the difficulty for segmenting images. So we introduced the Chan-Vese active contours model for image segmentation to detect the objects in given image, which is built based on techniques of curve evolution and level set method. The Chan-Vese model is a special case of Mumford-Shah functional for segmentation and level sets. It differs from other active contour models in that it is not edge dependent, therefore it is more capable of detecting objects whose boundaries may not be defined by a gradient. Finally, we developed code in Matlab 7.8 for solving resulting Partial differential equation numerically by the finite differences schemes on pixel-by-pixel domain.
Imagen: Photorealistic Text-to-Image Diffusion Models with Deep Language Unde...Vitaly Bondar
1. This document describes Imagen, a new state-of-the-art photorealistic text-to-image diffusion model with deep language understanding.
2. Key contributions include using large frozen language models as effective text encoders, a new dynamic thresholding sampling technique for more photorealistic images, and an efficient U-Net architecture.
3. On various benchmarks including COCO FID and a new DrawBench, human evaluations found Imagen generates images that better align with text prompts and outperform other models including DALL-E 2.
IMAGE CAPTIONING USING TRANSFORMER: VISIONAIDIRJET Journal
The document proposes a new image captioning model called VisionAid that aims to address several issues with existing approaches. It conducts a literature review of transformer-based image captioning methods to identify solutions. VisionAid incorporates grid-level feature extraction, augmented training data diversity using BERT embeddings, and a combination of normalized self-attention and geometric self-attention to better model object relationships while avoiding internal covariate shift issues. The model aims to generate more accurate and diverse captions by leveraging techniques from various transformer models discussed in the literature review.
A PROJECT REPORT ON REMOVAL OF UNNECESSARY OBJECTS FROM PHOTOS USING MASKINGIRJET Journal
This document presents a project report on removing unnecessary objects from photos using masking techniques. It discusses using algorithms like Fast Marching and Navier-Stokes to fill in missing image data and maintain continuity across boundaries. The Fast Marching method begins at region boundaries and works inward, prioritizing completion of boundary pixels first. Navier-Stokes uses fluid dynamics equations to continue intensity value functions and ensure they remain continuous at boundaries. Color filtering can also be used to segment specific colored objects or regions. The project aims to implement these techniques to remove unwanted objects from images and fill the resulting gaps seamlessly.
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.
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In this project, we consider the deep learning-based approaches to performing Neural Style Transfer (NST) on images. In particular, we intend to assess the Real-Time performance of this approach, since it has become a trending topic both in academia and in industrial applications.
For this purpose, after exploring the perceptual loss concept, which is used by the majority of models when performing NST, we conducted a review on a range of existing methods for this practical problem. We found that the feedforward based methods allow to achieve real time performance as opposed to the framework of iterative optimization proposed in the original Neural Style Transfer algorithm introduced by Gatys et al. Which is why we mainly focused on two feed-forward methods proposed in the literature: one that focuses on Single-Style transfer, TransformNet, and one that tackles the more generic problem of Multiple Style Transfer, MSG-Net.
This document summarizes a student project report on neural style transfer. The students tested existing feed-forward neural style transfer methods (TransformNet and MSG-Net) and compared their real-time performance and visual quality. They also experimented with combining multiple styles using the original optimization-based neural style transfer algorithm. The document provides background on neural style transfer techniques, discusses the methods tested, and outlines the project's methodology for evaluating and comparing the methods.
Ieee projects 2012 2013 - Digital Image ProcessingK Sundaresh Ka
ieee projects download, base paper for ieee projects, ieee projects list, ieee projects titles, ieee projects for cse, ieee projects on networking,ieee projects 2012, ieee projects 2013, final year project, computer science final year projects, final year projects for information technology, ieee final year projects, final year students projects, students projects in java, students projects download, students projects in java with source code, students projects architecture, free ieee papers
Medial Axis Transformation based Skeletonzation of Image Patterns using Image...IOSR Journals
1) The document discusses extracting the medial axis transform (MAT) of an image pattern using the Euclidean distance transform. The image is first converted to binary, then the Euclidean distance transform is used to compute the distance of each non-zero pixel to the closest zero pixel.
2) The medial axis transform represents the core or skeleton of an image pattern. There are different algorithms for extracting the skeleton or medial axis, including sequential and parallel algorithms. The skeleton provides a simple representation that preserves topological and size characteristics of the original shape.
3) The document provides background on medial axis transforms and different skeletonization algorithms. It then describes preparing the binary image and applying the Euclidean distance transform to extract the MAT and skeleton
An improved image compression algorithm based on daubechies wavelets with ar...Alexander Decker
This document summarizes an academic article that proposes a new image compression algorithm using Daubechies wavelets and arithmetic coding. It first discusses existing image compression techniques and their limitations. It then describes the proposed algorithm, which applies Daubechies wavelet transform followed by 2D Walsh wavelet transform on image blocks and arithmetic coding. Results show the proposed method achieves higher compression ratios and PSNR values than existing algorithms like EZW and SPIHT. Future work aims to improve results by exploring different wavelets and compression techniques.
This document provides information about Elysium Technologies Private Limited, an ISO 9001:2008 certified research and development company located in Singapore, Madurai, Trichy, Coimbatore, Kollam, and Cochin. It lists their branch office locations and contact information. The document then provides a list of 12 digital image processing projects available for the 2012-2013 academic year.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
An Intelligent approach to Pic to Cartoon Conversion using White-box-cartooni...IRJET Journal
This document presents an intelligent approach for converting photographs to cartoons. It proposes extracting three representations from images - the surface representation containing smooth surfaces, the structure representation containing thin color blocks and flattened surfaces, and the texture representation containing high-frequency textures and contours. A generative adversarial network is trained on these extracted representations to generate cartoonized images. The approach is implemented in a web application that allows users to upload images and obtain cartoonized outputs in a few seconds. Quantitative and qualitative evaluations demonstrate the approach outperforms previous methods.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
The document proposes a new framework called structure-modulated sparse representation (SMSR) for single image super-resolution. Existing super-resolution methods increase artifacts and do not consider image structure. The proposed SMSR algorithm formulates an optimization problem using gradient priors and nonlocal sparsity to reconstruct high-resolution images. It exploits multi-scale similarity using multi-step magnification and ridge regression for initial estimation. The algorithm also incorporates gradient histogram preservation as a regularization term. Experimental results show the proposed method outperforms state-of-the-art methods in recovering fine structures and details from low-resolution images.
This document discusses image compression using discrete wavelet transform (DWT) and principal component analysis (PCA). It first reviews several related works that use transforms like curvelet, wavelet and discrete cosine transform for image compression. It then describes preprocessing the input image using DWT to decompose it into sub-bands, and applying PCA on the high-frequency sub-bands to reduce dimensions and compress the image while preserving important boundaries. The algorithm is implemented and evaluated based on metrics like peak signal-to-noise ratio, standard deviation and entropy. Results show 95% accuracy in image identification from a database, though processing time increases significantly with database size.
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
IEEE Final Year Projects 2011-2012 :: Elysium Technologies Pvt Ltd::Imageproc...sunda2011
The document is a list of 13 image processing projects from 2011-2012 by Elysium Technologies Private Limited. It includes projects on 1D transforms for motion compensation residuals, edge preserving MAP estimation of images, a generalized unsharp masking algorithm, optimal design of color filter arrays, text detection in natural scenes, contrast-tone mapping, subspace optimization for image restoration, joint image registration and fusion, an easy path wavelet transform for image approximation, 3D color histogram equalization with uniform 1D grayscale histogram, camera calibration using spheres, estimating illumination chromaticity and correspondence, and variational histogram transfer of color images.
Orthogonal Matching Pursuit in 2D for Java with GPGPU ProspectivesMatt Simons
This document summarizes a project that implemented the Orthogonal Matching Pursuit algorithm in two dimensions (OMP2D) in Java and created an ImageJ plugin to apply it. It discusses the algorithm, details the Java implementation and optimizations, and proposes methods for accelerating it using GPUs. The author created a fully functional OMP2D ImageJ plugin with good performance compared to other implementations. The open source software and documentation are publicly available. The document outlines how further speed improvements could be achieved through mass parallelization on GPUs.
Image segmentation Based on Chan-Vese Active Contours using Finite Difference...ijsrd.com
There are a lot of image segmentation techniques that try to differentiate between backgrounds and object pixels but many of them fail to discriminate between different objects that are close to each other, e.g. low contrast between foreground and background regions increase the difficulty for segmenting images. So we introduced the Chan-Vese active contours model for image segmentation to detect the objects in given image, which is built based on techniques of curve evolution and level set method. The Chan-Vese model is a special case of Mumford-Shah functional for segmentation and level sets. It differs from other active contour models in that it is not edge dependent, therefore it is more capable of detecting objects whose boundaries may not be defined by a gradient. Finally, we developed code in Matlab 7.8 for solving resulting Partial differential equation numerically by the finite differences schemes on pixel-by-pixel domain.
Imagen: Photorealistic Text-to-Image Diffusion Models with Deep Language Unde...Vitaly Bondar
1. This document describes Imagen, a new state-of-the-art photorealistic text-to-image diffusion model with deep language understanding.
2. Key contributions include using large frozen language models as effective text encoders, a new dynamic thresholding sampling technique for more photorealistic images, and an efficient U-Net architecture.
3. On various benchmarks including COCO FID and a new DrawBench, human evaluations found Imagen generates images that better align with text prompts and outperform other models including DALL-E 2.
IMAGE CAPTIONING USING TRANSFORMER: VISIONAIDIRJET Journal
The document proposes a new image captioning model called VisionAid that aims to address several issues with existing approaches. It conducts a literature review of transformer-based image captioning methods to identify solutions. VisionAid incorporates grid-level feature extraction, augmented training data diversity using BERT embeddings, and a combination of normalized self-attention and geometric self-attention to better model object relationships while avoiding internal covariate shift issues. The model aims to generate more accurate and diverse captions by leveraging techniques from various transformer models discussed in the literature review.
A PROJECT REPORT ON REMOVAL OF UNNECESSARY OBJECTS FROM PHOTOS USING MASKINGIRJET Journal
This document presents a project report on removing unnecessary objects from photos using masking techniques. It discusses using algorithms like Fast Marching and Navier-Stokes to fill in missing image data and maintain continuity across boundaries. The Fast Marching method begins at region boundaries and works inward, prioritizing completion of boundary pixels first. Navier-Stokes uses fluid dynamics equations to continue intensity value functions and ensure they remain continuous at boundaries. Color filtering can also be used to segment specific colored objects or regions. The project aims to implement these techniques to remove unwanted objects from images and fill the resulting gaps seamlessly.
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.
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The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
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This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
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1. **Time Slots Allocation**: The core principle of TDM is to assign distinct time slots to each signal. During each time slot, the respective signal is transmitted, and then the process repeats cyclically. For example, if there are four signals to be transmitted, the TDM cycle will divide time into four slots, each assigned to one signal.
2. **Synchronization**: Synchronization is crucial in TDM systems to ensure that the signals are correctly aligned with their respective time slots. Both the transmitter and receiver must be synchronized to avoid any overlap or loss of data. This synchronization is typically maintained by a clock signal that ensures time slots are accurately aligned.
3. **Frame Structure**: TDM data is organized into frames, where each frame consists of a set of time slots. Each frame is repeated at regular intervals, ensuring continuous transmission of data streams. The frame structure helps in managing the data streams and maintaining the synchronization between the transmitter and receiver.
4. **Multiplexer and Demultiplexer**: At the transmitting end, a multiplexer combines multiple input signals into a single composite signal by assigning each signal to a specific time slot. At the receiving end, a demultiplexer separates the composite signal back into individual signals based on their respective time slots.
### Types of TDM
1. **Synchronous TDM**: In synchronous TDM, time slots are pre-assigned to each signal, regardless of whether the signal has data to transmit or not. This can lead to inefficiencies if some time slots remain empty due to the absence of data.
2. **Asynchronous TDM (or Statistical TDM)**: Asynchronous TDM addresses the inefficiencies of synchronous TDM by allocating time slots dynamically based on the presence of data. Time slots are assigned only when there is data to transmit, which optimizes the use of the communication channel.
### Applications of TDM
- **Telecommunications**: TDM is extensively used in telecommunication systems, such as in T1 and E1 lines, where multiple telephone calls are transmitted over a single line by assigning each call to a specific time slot.
- **Digital Audio and Video Broadcasting**: TDM is used in broadcasting systems to transmit multiple audio or video streams over a single channel, ensuring efficient use of bandwidth.
- **Computer Networks**: TDM is used in network protocols and systems to manage the transmission of data from multiple sources over a single network medium.
### Advantages of TDM
- **Efficient Use of Bandwidth**: TDM all
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Embedded machine learning-based road conditions and driving behavior monitoring
An approach toward fast gradient based image segmentation
1. AN APPROACH TOWARD FAST GRADIENT-BASED IMAGE SEGMENTATION
ABSTRACT
We present and investigate an approach to fast multi label color image segmentation
usingconvex optimization techniques. The presented model is in someways related to the well-
known Mumford–Shah model, butdeviates in certain important aspects. The optimization
problemhas been designed with two goals in mind. The objective functionshould represent
fundamental concepts of image segmentation,such as incorporation of weighted curve length and
variationof intensity in the segmented regions, while allowing transformationinto a convex
concave saddle point problem that iscomputationally inexpensive to solve. This paper
introducessuch a model, the nontrivial transformation of this model intoa convex–concave saddle
point problem, and the numericaltreatment of the problem. We evaluate our approach by
applyingour algorithm to various images and show that our resultsare competitive in terms of
quality at unprecedentedly lowcomputation times. Our algorithm allows high-quality
segmentationof megapixel images in a few seconds and achieves interactiveperformance for low
resolution.