This document summarizes the evolution of artistic style transfer techniques from early neural algorithms to real-time applications. It begins by describing the foundational "Neural Algorithm of Artistic Style" paper by Gatys et al. that introduced using convolutional neural networks to separate the content and style of images. It then discusses advancements that enabled real-time style transfer, including the work of Johnson et al. that incorporated perceptual losses to improve speed while maintaining quality. Finally, it mentions the Adaptive Instance Normalization method of Huang and Belongie that provides flexibility in real-time style adaptation.
IRJET- Neural Style based Comics Photo-Caption GeneratorIRJET Journal
This document proposes a method to automatically generate comic book strips from ordinary photographs by using neural style transfer to convert the photos to a comic-style and generating poetic captions to describe the comic images. It first discusses existing neural style transfer techniques for transferring artistic styles onto photos. It then focuses on adapting these methods to specifically transfer a comic book style. The proposed system uses a convolutional neural network to separate the content and style of images and recombine them to generate comic-style images, along with using a generative adversarial network to produce captions matching the comic images. The goal is to automate key aspects of the comic book creation process by stylizing real photos as comics and generating accompanying text.
IRJET- Concepts, Methods and Applications of Neural Style Transfer: A Rev...IRJET Journal
This document summarizes a research article that reviews concepts, methods, and applications of neural style transfer. It begins by defining neural style transfer as a technique that allows copying the style of one image and applying it to the content of another image. It then reviews relevant literature on neural style transfer and identifies gaps. Applications discussed include artistic image generation, data augmentation, and potentially machine creativity. The document outlines an implementation of neural style transfer using deep convolutional networks and analyzes results. It concludes that neural style transfer can provide insights into human visual perception and has promising applications.
Automated Image Captioning – Model Based on CNN – GRU ArchitectureIRJET Journal
This document presents a model for automated image captioning using deep learning techniques. The model uses a CNN-GRU architecture, where a CNN encoder extracts image features and a GRU decoder generates captions. The model is trained on the Flickr30K dataset and achieves a BLEU score of 0.5625. Experimental results show the model can accurately identify objects, animals, and relationships between objects in images and generate descriptive captions. The authors integrate text-to-speech functionality to help describe images to visually impaired people. In under 3 sentences, the document introduces an image captioning model using CNN-GRU, discusses training on Flickr30K, and highlights integration of text-to-speech for assisting the visually impaired.
IRJET - Deep Learning Approach to Inpainting and Outpainting SystemIRJET Journal
This document discusses a deep learning approach for image inpainting and outpainting. It proposes a new generative model-based approach using a fully convolutional neural network that can process images with multiple holes at variable locations and sizes. The model aims to not only synthesize novel image structures, but also explicitly utilize surrounding image features as references during training to generate better predictions. Experiments on faces, textures and natural images demonstrate the proposed approach generates higher quality inpainting results than existing methods. It aims to address limitations of CNNs in borrowing information from distant areas by leveraging texture and patch synthesis approaches.
IRJET - Content based Image ClassificationIRJET Journal
The document discusses content based image classification, which involves grouping large numbers of digital images uploaded daily into categories based on their visual content. It describes how content based image classification systems work by extracting features from images like shape, color, and texture to classify them. The document also outlines some challenges in content based image classification and potential areas of future research like using deep learning approaches.
Cartoonization of images using machine LearningIRJET Journal
The document presents a method for cartoonization of images using machine learning. It discusses converting real-world photos into cartoon images using a GAN-based approach. The key steps include:
1. Importing required modules like OpenCV, NumPy for image processing and GAN modeling.
2. Pre-processing input images by converting them to grayscale, smoothing, and edge detection.
3. Training a GAN using cartoon and photo images to generate new cartoon images.
4. For video cartoonization, frames are extracted from videos using OpenCV, individually cartoonized using the GAN, and reconstructed into a cartoon video.
The proposed system is able to convert images and videos to cartoon style in real-time using deep learning
The content based Image Retrieval is the restoration of images with respect to the visual appearances
like texture, shape and color.The methods, components and the algorithms adopted in this content based
retrieval of images were commonly derived from the areas like pattern identification, signal progressing
and the computer vision. Moreover the shape and the color features were abstracted in the course of
wavelet transformation and color histogram. Thus the new content based retrieval is proposed in this
research paper.In this paper the algorithms were required to propose with regards to the shape, shade and
texture feature abstraction .The concept of discrete wavelet transform to be implemented in order to
compute the Euclidian distance.The calculation of clusters was made with the help of the modified KMeans
clustering technique. Thus the analysis is made in among the query image and the database
image.The MATLAB software is implemented to execute the queries. The K-Means of abstraction is
proposed by performing fragmentation and grid-means module, feature extraction and K- nearest neighbor
clustering algorithms to construct the content based image retrieval system.Thus the obtained result are
made to compute and compared to all other algorithm for the retrieval of quality image features
Human Action Recognition using Contour History Images and Neural Networks Cla...IRJET Journal
This document proposes a new method for human action recognition using contour history images extracted from silhouettes, tracking of the body's center movement, and the relative dimensions of the bounding box containing each contour history image. Features are extracted and reduced using three different methods: dividing the contour history images into rectangles, a shallow autoencoder neural network, and a deep autoencoder neural network. The reduced features are classified using a neural network classifier. The proposed method achieved a recognition rate of 98.9% on a standard human action dataset, demonstrating its potential for real-time human action recognition applications.
IRJET- Neural Style based Comics Photo-Caption GeneratorIRJET Journal
This document proposes a method to automatically generate comic book strips from ordinary photographs by using neural style transfer to convert the photos to a comic-style and generating poetic captions to describe the comic images. It first discusses existing neural style transfer techniques for transferring artistic styles onto photos. It then focuses on adapting these methods to specifically transfer a comic book style. The proposed system uses a convolutional neural network to separate the content and style of images and recombine them to generate comic-style images, along with using a generative adversarial network to produce captions matching the comic images. The goal is to automate key aspects of the comic book creation process by stylizing real photos as comics and generating accompanying text.
IRJET- Concepts, Methods and Applications of Neural Style Transfer: A Rev...IRJET Journal
This document summarizes a research article that reviews concepts, methods, and applications of neural style transfer. It begins by defining neural style transfer as a technique that allows copying the style of one image and applying it to the content of another image. It then reviews relevant literature on neural style transfer and identifies gaps. Applications discussed include artistic image generation, data augmentation, and potentially machine creativity. The document outlines an implementation of neural style transfer using deep convolutional networks and analyzes results. It concludes that neural style transfer can provide insights into human visual perception and has promising applications.
Automated Image Captioning – Model Based on CNN – GRU ArchitectureIRJET Journal
This document presents a model for automated image captioning using deep learning techniques. The model uses a CNN-GRU architecture, where a CNN encoder extracts image features and a GRU decoder generates captions. The model is trained on the Flickr30K dataset and achieves a BLEU score of 0.5625. Experimental results show the model can accurately identify objects, animals, and relationships between objects in images and generate descriptive captions. The authors integrate text-to-speech functionality to help describe images to visually impaired people. In under 3 sentences, the document introduces an image captioning model using CNN-GRU, discusses training on Flickr30K, and highlights integration of text-to-speech for assisting the visually impaired.
IRJET - Deep Learning Approach to Inpainting and Outpainting SystemIRJET Journal
This document discusses a deep learning approach for image inpainting and outpainting. It proposes a new generative model-based approach using a fully convolutional neural network that can process images with multiple holes at variable locations and sizes. The model aims to not only synthesize novel image structures, but also explicitly utilize surrounding image features as references during training to generate better predictions. Experiments on faces, textures and natural images demonstrate the proposed approach generates higher quality inpainting results than existing methods. It aims to address limitations of CNNs in borrowing information from distant areas by leveraging texture and patch synthesis approaches.
IRJET - Content based Image ClassificationIRJET Journal
The document discusses content based image classification, which involves grouping large numbers of digital images uploaded daily into categories based on their visual content. It describes how content based image classification systems work by extracting features from images like shape, color, and texture to classify them. The document also outlines some challenges in content based image classification and potential areas of future research like using deep learning approaches.
Cartoonization of images using machine LearningIRJET Journal
The document presents a method for cartoonization of images using machine learning. It discusses converting real-world photos into cartoon images using a GAN-based approach. The key steps include:
1. Importing required modules like OpenCV, NumPy for image processing and GAN modeling.
2. Pre-processing input images by converting them to grayscale, smoothing, and edge detection.
3. Training a GAN using cartoon and photo images to generate new cartoon images.
4. For video cartoonization, frames are extracted from videos using OpenCV, individually cartoonized using the GAN, and reconstructed into a cartoon video.
The proposed system is able to convert images and videos to cartoon style in real-time using deep learning
The content based Image Retrieval is the restoration of images with respect to the visual appearances
like texture, shape and color.The methods, components and the algorithms adopted in this content based
retrieval of images were commonly derived from the areas like pattern identification, signal progressing
and the computer vision. Moreover the shape and the color features were abstracted in the course of
wavelet transformation and color histogram. Thus the new content based retrieval is proposed in this
research paper.In this paper the algorithms were required to propose with regards to the shape, shade and
texture feature abstraction .The concept of discrete wavelet transform to be implemented in order to
compute the Euclidian distance.The calculation of clusters was made with the help of the modified KMeans
clustering technique. Thus the analysis is made in among the query image and the database
image.The MATLAB software is implemented to execute the queries. The K-Means of abstraction is
proposed by performing fragmentation and grid-means module, feature extraction and K- nearest neighbor
clustering algorithms to construct the content based image retrieval system.Thus the obtained result are
made to compute and compared to all other algorithm for the retrieval of quality image features
Human Action Recognition using Contour History Images and Neural Networks Cla...IRJET Journal
This document proposes a new method for human action recognition using contour history images extracted from silhouettes, tracking of the body's center movement, and the relative dimensions of the bounding box containing each contour history image. Features are extracted and reduced using three different methods: dividing the contour history images into rectangles, a shallow autoencoder neural network, and a deep autoencoder neural network. The reduced features are classified using a neural network classifier. The proposed method achieved a recognition rate of 98.9% on a standard human action dataset, demonstrating its potential for real-time human action recognition applications.
IRJET - Conversion of Ancient Tamil Characters to Modern Tamil CharactersIRJET Journal
This document discusses a proposed system for converting ancient Tamil characters from stone inscriptions to modern Tamil characters. It begins with an introduction describing the need for such a system given that ancient Tamil script differs from modern script. It then reviews related work on image processing techniques. The proposed system is described as collecting a database of ancient characters, preprocessing images through noise removal, and recognizing characters using morphological operations and matching to a corpus of modern Tamil characters. The goal is to help modern readers understand ancient texts by converting scripts.
1. The document summarizes a student project that aims to create a virtual try-on application using augmented reality. It surveys existing methods for tasks like clothing segmentation, human pose estimation, and virtual try-on that could be used to build the application.
2. It discusses approaches the students investigated like using depth cameras for measurements, non-depth based methods using computer vision, parsing clothes and humans, and existing work on 2D virtual try-on.
3. The students implemented initial modules for their pipeline including a U-Net for clothing segmentation trained on images and masks from the Viton dataset.
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.
1. The document presents an approach to enhance the realism of synthetic images rendered by game engines. A convolutional network is trained to modify rendered images using intermediate representations from the rendering process.
2. The network is trained with an adversarial objective to provide strong supervision at multiple perceptual levels. A new strategy is proposed for sampling image patches during training to address differences in scene layout distributions between datasets.
3. The approach significantly enhances photorealism over recent image-to-image translation methods and baselines, as shown in controlled experiments. It can add realistic details like gloss, vegetation, and road textures while keeping enhancements consistent with the input image content.
A Review on Matching For Sketch TechniqueIOSR Journals
This document summarizes several techniques for sketch-based image retrieval. It discusses methods using SIFT features, HOG descriptors, color segmentation, and gradient orientation histograms. It also reviews applications of these techniques to domains like facial recognition, graffiti matching, and tattoo identification for law enforcement. The techniques aim to extract visual features from sketches that can be used to match and retrieve similar images from databases. While achieving good results, the methods have limitations regarding database size and specificity, and accuracy with complex textures and shapes. Overall, the review examines advances in using sketches as queries for image retrieval.
A Graph-based Web Image Annotation for Large Scale Image RetrievalIRJET Journal
1) The document proposes a graph-based framework called Web Image Annotation for Large Scale Image Retrieval to improve the accuracy of automatic image annotation.
2) The framework first identifies a set of visually similar images from a large image database to label a query image, then applies a graph pattern matching algorithm to find representative keywords from the annotations of similar images.
3) The approach is extended to Probabilistic Reverse Annotation to rank relevant images, which takes the novel approach of matching keywords to images rather than images to keywords to improve annotation performance for large datasets.
IRJET- Art Authentication System using Deep Neural NetworksIRJET Journal
1) The document presents a system to authenticate paintings by artists using deep convolutional neural networks. The system processes images through thousands of neurons to extract patterns and characteristics of an artist's style.
2) A deep convolutional neural network model is implemented and trained on datasets of labeled artworks. The network aims to classify new paintings by artist with 80% accuracy, higher than previous methods.
3) The system was tested on 5 paintings, with a confusion matrix showing correct and incorrect classifications. The 80% accuracy rate is an improvement over previous techniques, but the model has limitations as the number of paintings increases.
Thai culture image classification with transfer learningIJECEIAES
Classifying images of Thai culture is important for a variety of applications, such as tourism, education, and cultural preservation. However, building a Machine learning model from scratch to classify Thai cultural images can be challenging due to the limited availability of annotated data. In this study, we investigate the use of transfer learning for the task of image classification on a dataset of Thai cultural images. We utilize three popular convolutional neural network models, namely MobileNet, EfficientNet, and residual network (ResNet) as baseline pre-trained models. Their performances were evaluated when they were trained from random initialization, used as a feature extractor, and fully fine-tuned. The results showed that all three models performed better in terms of accuracy and training time when they were used as a feature extractor, with EfficientNet achieving the highest accuracy of 95.87% while maintaining the training time of 24 ms/iteration. To better understand the reasoning behind the predictions made by the models, we deployed the gradient-weighted class activation mapping (Grad-CAM) visualization technique to generate heatmaps that the models attend to when making predictions. Both our quantitative and qualitative experiments demonstrated that transfer learning is an effective approach to image classification on Thai cultural images.
IRJET- A Vision based Hand Gesture Recognition System using Convolutional...IRJET Journal
This document describes a vision-based hand gesture recognition system using convolutional neural networks. The system captures images of hand gestures using a camera, pre-processes the images, and classifies the gestures using a CNN model. The CNN architecture includes convolutional layers, max pooling layers, dropout layers, and fully connected layers. The system was trained on a dataset of images representing 7 different hand gestures. Testing achieved over 90% accuracy in recognizing the gestures. This vision-based approach allows for natural human-computer interaction without physical devices.
Image Captioning Generator using Deep Machine Learningijtsrd
Technologys scope has evolved into one of the most powerful tools for human development in a variety of fields.AI and machine learning have become one of the most powerful tools for completing tasks quickly and accurately without the need for human intervention. This project demonstrates how deep machine learning can be used to create a caption or a sentence for a given picture. This can be used for visually impaired persons, as well as automobiles for self identification, and for various applications to verify quickly and easily. The Convolutional Neural Network CNN is used to describe the alphabet, and the Long Short Term Memory LSTM is used to organize the right meaningful sentences in this model. The flicker 8k and flicker 30k datasets were used to train this. Sreejith S P | Vijayakumar A "Image Captioning Generator using Deep Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42344.pdf Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42344/image-captioning-generator-using-deep-machine-learning/sreejith-s-p
An Efficient Image Forensic Mechanism using Super Pixel by SIFT and LFP Algor...IRJET Journal
This document summarizes a research paper that proposes an efficient image forensic mechanism using super pixels, scale-invariant feature transform (SIFT), and local fingerprint (LFP) algorithm to detect copy-move forgery. The mechanism applies wavelet decomposition to compute super pixel sizes for segmentation, extracts features using SIFT, and performs region growing to detect forged regions. Experimental results showed increased performance in precision, sensitivity, specificity, and F1 score measures for forgery detection compared to existing techniques. The document also reviews several related works on image forgery detection techniques.
DragGAN is a new AI image editing tool that lets you manipulate images with simple drag controls developed by researchers at the University of California, Berkeley.
It uses generative AI to create realistic changes to the structure and appearance of objects in images. You can also rotate images as if they were 3D models.
The user can then use a drag-and-drop interface to edit the image. DragGAN will then generate a new image that reflects the user's edits.
IRJET- Real Time Implementation of Bi-Histogram Equalization Method on Androi...IRJET Journal
This document discusses implementing bi-histogram equalization for contrast enhancement on the Android platform. It begins with an introduction to histogram equalization and its drawback of changing image brightness. It then presents bi-histogram equalization as an approach to overcome this by decomposing the image into two sub-images based on the mean and equalizing them independently to preserve the mean brightness. The paper outlines implementing various steps like image acquisition, preprocessing, and bi-histogram equalization on Android. It shows output images with enhanced visibility compared to the originals, avoiding the flattening property of standard histogram equalization.
IRJET- Design and Implementation of ATM Security System using Vibration Senso...IRJET Journal
This document discusses implementing bi-histogram equalization for contrast enhancement on the Android platform. It begins with an introduction to histogram equalization and its drawback of changing image brightness. It then presents bi-histogram equalization as an approach to overcome this by decomposing the image into two sub-images based on the mean and equalizing them independently to preserve the mean brightness. The paper outlines implementing various steps like image acquisition, preprocessing, and bi-histogram equalization on Android. It shows output images with enhanced visibility compared to the originals, avoiding the flattening property of standard histogram equalization.
Channel and spatial attention mechanism for fashion image captioning IJECEIAES
The document proposes a novel model for fashion image captioning that incorporates two attention mechanisms: spatial attention and channel-wise attention. The model uses an encoder-decoder framework with a CNN encoder to extract image features and an RNN decoder to generate captions. Channel-wise attention focuses on extracting distinct features from different channels to capture texture or pattern, while spatial attention encodes context of each pixel to identify objects. The combined attention mechanisms allow the model to dynamically focus on spatial or attribute information when generating captions. Evaluation on the Fashion-Gen dataset shows the proposed approach outperforms other methods and generates captions describing fashion item attributes.
06108870 analytical study of parallel and distributed image processing 2011Kiran Verma
This document summarizes an analytical study of parallel and distributed image processing. It discusses how parallelism can be applied to image processing through data parallelism, task parallelism, and pipeline parallelism. It also describes common architectures for parallel processing like using parallel hardware or distributed computing. Finally, it analyzes tools and technologies used for parallel image processing like MPI, OpenMP, and CUDA and discusses application domains and ongoing research areas in this field.
IRJET- Transformation of Realistic Images and Videos into Cartoon Images and ...IRJET Journal
This document summarizes research on using a Generative Adversarial Network (GAN) called Cartoon GAN to transform real-world images and videos into cartoon images and videos. The researchers trained Cartoon GAN on 3000 real-world images to learn how to generate cartoon images by using content and adversarial loss functions. They were able to successfully convert both individual images and video clips into cartoon/animated versions. For video, they used the OpenCV library to divide videos into frames, pass each frame through the trained Cartoon GAN model, and then recombine the cartoonized frames into an output cartoon video. The researchers concluded that Cartoon GAN is an effective method for automatically transforming real media into cartoons and aims to improve the quality and resolution
A Survey on Perceptual image hash for authentication of contentIRJET Journal
This document summarizes research on perceptual image hashing for content authentication. It discusses how perceptual hashing extracts visually sensitive features based on the human visual system to generate robust hashes that can identify malicious alterations while being sensitive to perceptual changes. The document reviews related work on image hashing and fingerprinting techniques. It also explains how the proposed method aims to achieve a balance between robustness to content-preserving distortions and sensitivity to detect malicious tampering, as well as the ability to localize compromised regions of an image.
A Pointing Gesture-based Signal to Text Communication System Using OpenCV in ...IRJET Journal
This document presents a system for real-time pointing gesture tracking and recognition using computer vision techniques in OpenCV and Python. The system detects a colored fingertip in video frames and applies optical character recognition to recognize the intended text. It tracks the fingertip contour across frames, stores the coordinates, and draws the trajectory to convert gestures to text without requiring additional hardware inputs. While the current system works well, it is limited by being sensitive to other colored objects in the background that could interfere with fingertip detection. Overall, the paper proposes and discusses an air writing system using computer vision to enable natural human-computer interaction through gesture recognition.
This document compares the results of retrieving songket motifs from a digital repository using a sketching technique versus a keyword technique. It finds that sketch-based retrieval was more successful, with 80% of sketch queries returning more relevant results than keyword queries. The document provides background on songket as Malaysian cultural heritage and discusses prior research on sketch-based image retrieval techniques. It evaluates existing songket websites and then describes the methodology, design, and development of a songket motif retrieval prototype using sketching.
TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
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Image Captioning Generator using Deep Machine Learningijtsrd
Technologys scope has evolved into one of the most powerful tools for human development in a variety of fields.AI and machine learning have become one of the most powerful tools for completing tasks quickly and accurately without the need for human intervention. This project demonstrates how deep machine learning can be used to create a caption or a sentence for a given picture. This can be used for visually impaired persons, as well as automobiles for self identification, and for various applications to verify quickly and easily. The Convolutional Neural Network CNN is used to describe the alphabet, and the Long Short Term Memory LSTM is used to organize the right meaningful sentences in this model. The flicker 8k and flicker 30k datasets were used to train this. Sreejith S P | Vijayakumar A "Image Captioning Generator using Deep Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd42344.pdf Paper URL: https://www.ijtsrd.comcomputer-science/artificial-intelligence/42344/image-captioning-generator-using-deep-machine-learning/sreejith-s-p
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This document discusses implementing bi-histogram equalization for contrast enhancement on the Android platform. It begins with an introduction to histogram equalization and its drawback of changing image brightness. It then presents bi-histogram equalization as an approach to overcome this by decomposing the image into two sub-images based on the mean and equalizing them independently to preserve the mean brightness. The paper outlines implementing various steps like image acquisition, preprocessing, and bi-histogram equalization on Android. It shows output images with enhanced visibility compared to the originals, avoiding the flattening property of standard histogram equalization.
Channel and spatial attention mechanism for fashion image captioning IJECEIAES
The document proposes a novel model for fashion image captioning that incorporates two attention mechanisms: spatial attention and channel-wise attention. The model uses an encoder-decoder framework with a CNN encoder to extract image features and an RNN decoder to generate captions. Channel-wise attention focuses on extracting distinct features from different channels to capture texture or pattern, while spatial attention encodes context of each pixel to identify objects. The combined attention mechanisms allow the model to dynamically focus on spatial or attribute information when generating captions. Evaluation on the Fashion-Gen dataset shows the proposed approach outperforms other methods and generates captions describing fashion item attributes.
06108870 analytical study of parallel and distributed image processing 2011Kiran Verma
This document summarizes an analytical study of parallel and distributed image processing. It discusses how parallelism can be applied to image processing through data parallelism, task parallelism, and pipeline parallelism. It also describes common architectures for parallel processing like using parallel hardware or distributed computing. Finally, it analyzes tools and technologies used for parallel image processing like MPI, OpenMP, and CUDA and discusses application domains and ongoing research areas in this field.
IRJET- Transformation of Realistic Images and Videos into Cartoon Images and ...IRJET Journal
This document summarizes research on using a Generative Adversarial Network (GAN) called Cartoon GAN to transform real-world images and videos into cartoon images and videos. The researchers trained Cartoon GAN on 3000 real-world images to learn how to generate cartoon images by using content and adversarial loss functions. They were able to successfully convert both individual images and video clips into cartoon/animated versions. For video, they used the OpenCV library to divide videos into frames, pass each frame through the trained Cartoon GAN model, and then recombine the cartoonized frames into an output cartoon video. The researchers concluded that Cartoon GAN is an effective method for automatically transforming real media into cartoons and aims to improve the quality and resolution
A Survey on Perceptual image hash for authentication of contentIRJET Journal
This document summarizes research on perceptual image hashing for content authentication. It discusses how perceptual hashing extracts visually sensitive features based on the human visual system to generate robust hashes that can identify malicious alterations while being sensitive to perceptual changes. The document reviews related work on image hashing and fingerprinting techniques. It also explains how the proposed method aims to achieve a balance between robustness to content-preserving distortions and sensitivity to detect malicious tampering, as well as the ability to localize compromised regions of an image.
A Pointing Gesture-based Signal to Text Communication System Using OpenCV in ...IRJET Journal
This document presents a system for real-time pointing gesture tracking and recognition using computer vision techniques in OpenCV and Python. The system detects a colored fingertip in video frames and applies optical character recognition to recognize the intended text. It tracks the fingertip contour across frames, stores the coordinates, and draws the trajectory to convert gestures to text without requiring additional hardware inputs. While the current system works well, it is limited by being sensitive to other colored objects in the background that could interfere with fingertip detection. Overall, the paper proposes and discusses an air writing system using computer vision to enable natural human-computer interaction through gesture recognition.
This document compares the results of retrieving songket motifs from a digital repository using a sketching technique versus a keyword technique. It finds that sketch-based retrieval was more successful, with 80% of sketch queries returning more relevant results than keyword queries. The document provides background on songket as Malaysian cultural heritage and discusses prior research on sketch-based image retrieval techniques. It evaluates existing songket websites and then describes the methodology, design, and development of a songket motif retrieval prototype using sketching.
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TUNNELING IN HIMALAYAS WITH NATM METHOD: A SPECIAL REFERENCES TO SUNGAL TUNNE...IRJET Journal
1) The document discusses the Sungal Tunnel project in Jammu and Kashmir, India, which is being constructed using the New Austrian Tunneling Method (NATM).
2) NATM involves continuous monitoring during construction to adapt to changing ground conditions, and makes extensive use of shotcrete for temporary tunnel support.
3) The methodology section outlines the systematic geotechnical design process for tunnels according to Austrian guidelines, and describes the various steps of NATM tunnel construction including initial and secondary tunnel support.
STUDY THE EFFECT OF RESPONSE REDUCTION FACTOR ON RC FRAMED STRUCTUREIRJET Journal
This study examines the effect of response reduction factors (R factors) on reinforced concrete (RC) framed structures through nonlinear dynamic analysis. Three RC frame models with varying heights (4, 8, and 12 stories) were analyzed in ETABS software under different R factors ranging from 1 to 5. The results showed that displacement increased as the R factor decreased, indicating less linear behavior for lower R factors. Drift also decreased proportionally with increasing R factors from 1 to 5. Shear forces in the frames decreased with higher R factors. In general, R factors of 3 to 5 produced more satisfactory performance with less displacement and drift. The displacement variations between different building heights were consistent at different R factors. This study evaluated how R factors influence
A COMPARATIVE ANALYSIS OF RCC ELEMENT OF SLAB WITH STARK STEEL (HYSD STEEL) A...IRJET Journal
This study compares the use of Stark Steel and TMT Steel as reinforcement materials in a two-way reinforced concrete slab. Mechanical testing is conducted to determine the tensile strength, yield strength, and other properties of each material. A two-way slab design adhering to codes and standards is executed with both materials. The performance is analyzed in terms of deflection, stability under loads, and displacement. Cost analyses accounting for material, durability, maintenance, and life cycle costs are also conducted. The findings provide insights into the economic and structural implications of each material for reinforcement selection and recommendations on the most suitable material based on the analysis.
Effect of Camber and Angles of Attack on Airfoil CharacteristicsIRJET Journal
This document discusses a study analyzing the effect of camber, position of camber, and angle of attack on the aerodynamic characteristics of airfoils. Sixteen modified asymmetric NACA airfoils were analyzed using computational fluid dynamics (CFD) by varying the camber, camber position, and angle of attack. The results showed the relationship between these parameters and the lift coefficient, drag coefficient, and lift to drag ratio. This provides insight into how changes in airfoil geometry impact aerodynamic performance.
A Review on the Progress and Challenges of Aluminum-Based Metal Matrix Compos...IRJET Journal
This document reviews the progress and challenges of aluminum-based metal matrix composites (MMCs), focusing on their fabrication processes and applications. It discusses how various aluminum MMCs have been developed using reinforcements like borides, carbides, oxides, and nitrides to improve mechanical and wear properties. These composites have gained prominence for their lightweight, high-strength and corrosion resistance properties. The document also examines recent advancements in fabrication techniques for aluminum MMCs and their growing applications in industries such as aerospace and automotive. However, it notes that challenges remain around issues like improper mixing of reinforcements and reducing reinforcement agglomeration.
Dynamic Urban Transit Optimization: A Graph Neural Network Approach for Real-...IRJET Journal
This document discusses research on using graph neural networks (GNNs) for dynamic optimization of public transportation networks in real-time. GNNs represent transit networks as graphs with nodes as stops and edges as connections. The GNN model aims to optimize networks using real-time data on vehicle locations, arrival times, and passenger loads. This helps increase mobility, decrease traffic, and improve efficiency. The system continuously trains and infers to adapt to changing transit conditions, providing decision support tools. While research has focused on performance, more work is needed on security, socio-economic impacts, contextual generalization of models, continuous learning approaches, and effective real-time visualization.
Structural Analysis and Design of Multi-Storey Symmetric and Asymmetric Shape...IRJET Journal
This document summarizes a research project that aims to compare the structural performance of conventional slab and grid slab systems in multi-story buildings using ETABS software. The study will analyze both symmetric and asymmetric building models under various loading conditions. Parameters like deflections, moments, shears, and stresses will be examined to evaluate the structural effectiveness of each slab type. The results will provide insights into the comparative behavior of conventional and grid slabs to help engineers and architects select appropriate slab systems based on building layouts and design requirements.
A Review of “Seismic Response of RC Structures Having Plan and Vertical Irreg...IRJET Journal
This document summarizes and reviews a research paper on the seismic response of reinforced concrete (RC) structures with plan and vertical irregularities, with and without infill walls. It discusses how infill walls can improve or reduce the seismic performance of RC buildings, depending on factors like wall layout, height distribution, connection to the frame, and relative stiffness of walls and frames. The reviewed research paper analyzes the behavior of infill walls, effects of vertical irregularities, and seismic performance of high-rise structures under linear static and dynamic analysis. It studies response characteristics like story drift, deflection and shear. The document also provides literature on similar research investigating the effects of infill walls, soft stories, plan irregularities, and different
This document provides a review of machine learning techniques used in Advanced Driver Assistance Systems (ADAS). It begins with an abstract that summarizes key applications of machine learning in ADAS, including object detection, recognition, and decision-making. The introduction discusses the integration of machine learning in ADAS and how it is transforming vehicle safety. The literature review then examines several research papers on topics like lightweight deep learning models for object detection and lane detection models using image processing. It concludes by discussing challenges and opportunities in the field, such as improving algorithm robustness and adaptability.
Long Term Trend Analysis of Precipitation and Temperature for Asosa district,...IRJET Journal
The document analyzes temperature and precipitation trends in Asosa District, Benishangul Gumuz Region, Ethiopia from 1993 to 2022 based on data from the local meteorological station. The results show:
1) The average maximum and minimum annual temperatures have generally decreased over time, with maximum temperatures decreasing by a factor of -0.0341 and minimum by -0.0152.
2) Mann-Kendall tests found the decreasing temperature trends to be statistically significant for annual maximum temperatures but not for annual minimum temperatures.
3) Annual precipitation in Asosa District showed a statistically significant increasing trend.
The conclusions recommend development planners account for rising summer precipitation and declining temperatures in
P.E.B. Framed Structure Design and Analysis Using STAAD ProIRJET Journal
This document discusses the design and analysis of pre-engineered building (PEB) framed structures using STAAD Pro software. It provides an overview of PEBs, including that they are designed off-site with building trusses and beams produced in a factory. STAAD Pro is identified as a key tool for modeling, analyzing, and designing PEBs to ensure their performance and safety under various load scenarios. The document outlines modeling structural parts in STAAD Pro, evaluating structural reactions, assigning loads, and following international design codes and standards. In summary, STAAD Pro is used to design and analyze PEB framed structures to ensure safety and code compliance.
A Review on Innovative Fiber Integration for Enhanced Reinforcement of Concre...IRJET Journal
This document provides a review of research on innovative fiber integration methods for reinforcing concrete structures. It discusses studies that have explored using carbon fiber reinforced polymer (CFRP) composites with recycled plastic aggregates to develop more sustainable strengthening techniques. It also examines using ultra-high performance fiber reinforced concrete to improve shear strength in beams. Additional topics covered include the dynamic responses of FRP-strengthened beams under static and impact loads, and the performance of preloaded CFRP-strengthened fiber reinforced concrete beams. The review highlights the potential of fiber composites to enable more sustainable and resilient construction practices.
Survey Paper on Cloud-Based Secured Healthcare SystemIRJET Journal
This document summarizes a survey on securing patient healthcare data in cloud-based systems. It discusses using technologies like facial recognition, smart cards, and cloud computing combined with strong encryption to securely store patient data. The survey found that healthcare professionals believe digitizing patient records and storing them in a centralized cloud system would improve access during emergencies and enable more efficient care compared to paper-based systems. However, ensuring privacy and security of patient data is paramount as healthcare incorporates these digital technologies.
Review on studies and research on widening of existing concrete bridgesIRJET Journal
This document summarizes several studies that have been conducted on widening existing concrete bridges. It describes a study from China that examined load distribution factors for a bridge widened with composite steel-concrete girders. It also outlines challenges and solutions for widening a bridge in the UAE, including replacing bearings and stitching the new and existing structures. Additionally, it discusses two bridge widening projects in New Zealand that involved adding precast beams and stitching to connect structures. Finally, safety measures and challenges for strengthening a historic bridge in Switzerland under live traffic are presented.
React based fullstack edtech web applicationIRJET Journal
The document describes the architecture of an educational technology web application built using the MERN stack. It discusses the frontend developed with ReactJS, backend with NodeJS and ExpressJS, and MongoDB database. The frontend provides dynamic user interfaces, while the backend offers APIs for authentication, course management, and other functions. MongoDB enables flexible data storage. The architecture aims to provide a scalable, responsive platform for online learning.
A Comprehensive Review of Integrating IoT and Blockchain Technologies in the ...IRJET Journal
This paper proposes integrating Internet of Things (IoT) and blockchain technologies to help implement objectives of India's National Education Policy (NEP) in the education sector. The paper discusses how blockchain could be used for secure student data management, credential verification, and decentralized learning platforms. IoT devices could create smart classrooms, automate attendance tracking, and enable real-time monitoring. Blockchain would ensure integrity of exam processes and resource allocation, while smart contracts automate agreements. The paper argues this integration has potential to revolutionize education by making it more secure, transparent and efficient, in alignment with NEP goals. However, challenges like infrastructure needs, data privacy, and collaborative efforts are also discussed.
A REVIEW ON THE PERFORMANCE OF COCONUT FIBRE REINFORCED CONCRETE.IRJET Journal
This document provides a review of research on the performance of coconut fibre reinforced concrete. It summarizes several studies that tested different volume fractions and lengths of coconut fibres in concrete mixtures with varying compressive strengths. The studies found that coconut fibre improved properties like tensile strength, toughness, crack resistance, and spalling resistance compared to plain concrete. Volume fractions of 2-5% and fibre lengths of 20-50mm produced the best results. The document concludes that using a 4-5% volume fraction of coconut fibres 30-40mm in length with M30-M60 grade concrete would provide benefits based on previous research.
Optimizing Business Management Process Workflows: The Dynamic Influence of Mi...IRJET Journal
The document discusses optimizing business management processes through automation using Microsoft Power Automate and artificial intelligence. It provides an overview of Power Automate's key components and features for automating workflows across various apps and services. The document then presents several scenarios applying automation solutions to common business processes like data entry, monitoring, HR, finance, customer support, and more. It estimates the potential time and cost savings from implementing automation for each scenario. Finally, the conclusion emphasizes the transformative impact of AI and automation tools on business processes and the need for ongoing optimization.
Multistoried and Multi Bay Steel Building Frame by using Seismic DesignIRJET Journal
The document describes the seismic design of a G+5 steel building frame located in Roorkee, India according to Indian codes IS 1893-2002 and IS 800. The frame was analyzed using the equivalent static load method and response spectrum method, and its response in terms of displacements and shear forces were compared. Based on the analysis, the frame was designed as a seismic-resistant steel structure according to IS 800:2007. The software STAAD Pro was used for the analysis and design.
Cost Optimization of Construction Using Plastic Waste as a Sustainable Constr...IRJET Journal
This research paper explores using plastic waste as a sustainable and cost-effective construction material. The study focuses on manufacturing pavers and bricks using recycled plastic and partially replacing concrete with plastic alternatives. Initial results found that pavers and bricks made from recycled plastic demonstrate comparable strength and durability to traditional materials while providing environmental and cost benefits. Additionally, preliminary research indicates incorporating plastic waste as a partial concrete replacement significantly reduces construction costs without compromising structural integrity. The outcomes suggest adopting plastic waste in construction can address plastic pollution while optimizing costs, promoting more sustainable building practices.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Batteries -Introduction – Types of Batteries – discharging and charging of battery - characteristics of battery –battery rating- various tests on battery- – Primary battery: silver button cell- Secondary battery :Ni-Cd battery-modern battery: lithium ion battery-maintenance of batteries-choices of batteries for electric vehicle applications.
Fuel Cells: Introduction- importance and classification of fuel cells - description, principle, components, applications of fuel cells: H2-O2 fuel cell, alkaline fuel cell, molten carbonate fuel cell and direct methanol fuel cells.
Understanding Inductive Bias in Machine LearningSUTEJAS
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.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.