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检索条件"任意字段=Proceedings of the 3rd International Conference on Video and Image Processing"

共 13072 条记录，以下是61-70 订阅

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proceedings - 2024 3rd international conference on Sentiment Analysis and Deep Learning, ICSADL 2024

Proceedings - 2024 3rd International Conference on Sentiment...

引用

3rd international conference on Sentiment Analysis and Deep Learning, ICSADL 2024

ISBN: (纸本)9798350396157

The proceedings contain 121 papers. The topics discussed include: ***: a cutting-edge solution for informed meal selection;a hybrid learning model for detecting attacks in cloud computing;a real time prediction model for round winners of counter strike: global offensive;social media censoring using of visual sentimental analyzer;a comparative analysis of machine learning and deep learning algorithms for skin cancer detection and classification: exploring performance across multiple parameters;an extensive review of intelligent deep learning based anomaly detection and classification of 3D MRI brain imaging data;evaluating human emotions using image processing and brain waves;and hybrid machine learning based shill bidding fraud detection system using recursive feature elimination method.

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Integrated Colorization and Styling Approach for Enhancing image Clarity 3

Integrated Colorization and Styling Approach for Enhancing I...

引用

3rd international conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Shalini, Gollapalli Madhu Anand, Rakam Sankeerth, Thalloju Reddy, H. Venkateswara Hariharan, Shanmugasundaram Kukreja, Vinay Vardhaman College of Engineering Department of Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350375190

image exploration adopts several dimensionalities with web-based tasks, integrating Streamlit and OpenCV to create an interactive platform for advanced image enhancement. Alongside the transformative tool enabling conversion of black and white images into vibrant compositions, an innovative styling suite offers diverse artistic filters. Notably, the addition of a camera option allows users to capture photos directly within the interface. Through Streamlit's intuitive interface and OpenCV's robust image processing, users experience real-time previews for seamless colorization and filtering. The proposed methodology involves designing a responsive web interface, optimizing Streamlit widgets for file uploads and style selection, and leveraging OpenCV for image processing. Results demonstrate the application's effectiveness, providing immediate insights into style impact. Challenges include processing speed optimization, with future research directions exploring advanced Machine Learning (ML) models for dynamic style transfer. In summary, this research advances interactive image processing, offering a refined platform for creative visual content enhancement. The results obtained is promising leading to effective image colorization and styling, thereby improving the quality of the image. © 2024 IEEE.

关键词： image enhancement

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Enhancing image Quality by Minimizing Specular Reflections via Dark Channel Prior 3

Enhancing Image Quality by Minimizing Specular Reflections v...

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3rd international conference on Applied Artificial Intelligence and Computing, ICAAIC 2024

作者： Janani, B. Krithikraj, V. Hirankumar, M. Kavibarath, G. K S Rangasamy College of Technology Department of Computer Science and Engineering Tamil Nadu India

ISBN: (纸本)9798350375190

The goal of blind picture deblurring, a challenging and demanding topic in image processing, is to restore the original, clear image from a deteriorated and blurry version without requiring prior knowledge either the blur kernel or the clean image. In this research, we describe an efficient approach to blind image deblurring that combines matrix-variable optimization with two-dimensional discrete wavelet transform (DWT) to provide better deblurring results. We can immediately optimize a matrix representation of the clean image thanks to the matrix-variable optimization framework, which allows for more accurate and efficient optimization. Additionally, by employing the DWT to divide the estimated clean picture matrix into many frequency sub bands, high-frequency noise components can be better deblurred by regularizing and denoising them. © 2024 IEEE.

关键词： Discrete wavelet transforms

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Face Recognition Attendance Framework using Quantum Edge processing 3

Face Recognition Attendance Framework using Quantum Edge Pro...

引用

3rd international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Rajarajeswari, S. Ranjitha, Hassan Srinivas Ramaiah Institute of Technology Bangalore India

ISBN: (纸本)9798331515911

Through the use of a Streamlit web application, the script is a highly intelligent tool that combines cutting-edge quantum processing principles with traditional computer vision approaches to handle a variety of face detection and identification tasks. While other libraries handle computer vision jobs and numerical calculations, such as NumPy and OpenCV, Streamlit is essential to developing the web application interface. While Streamlit WebRTC allows real-time video streaming, PIL is utilized for image processing. The application is set up to have a personalized look and a centered layout. Users may upload photographs, choose detection modes, and modify face detection settings on its header and sidebar. The program detects faces in uploaded photographs by encircling them with bounding boxes using the Haar Cascade Classifier. This may be used to build a face dataset or train a face recognition algorithm. Another important feature is real-time face identification, in which the software uses the Haar Cascade Classifier to identify faces in a video stream. Bounding boxes are used to emphasize faces, and photos containing faces are retained for later study or training. The program may utilize taken photographs to train a model for face recognition. These photos are processed, turned into grayscale, and then the LBPH (Local Binary Patterns Histograms) technique is used to train the model. The trained model is then kept for use in upcoming facial recognition assignments. Moreover, the program may be set up to track attendance in real time by identifying faces in a webcam stream. Time stamps are recorded, attendance is logged using recognized faces, and the information is saved to a CSV file. All things considered, the script provides a complete solution that combines traditional and quantum methods for real-time face identification, picture processing, and attendance monitoring. This makes it an adaptable tool for a range of computer vision and machine learning application

关键词： Photography

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Rate Control for Immersive video Depth Map Coding 3

Rate Control for Immersive Video Depth Map Coding

引用

3rd international conference on Signal image processing and Communication, ICSIPC 2023

作者： Shen, Xueyuan Chen, Jing Liu, Wei Zhou, Tingkai College of Information Science and Engineering Huaqiao University Xiamen361021 China

ISBN: (纸本)9781510670945

A novel rate control algorithm for immersive video depth map coding is proposed to ensure the immersive video quality in the context of limited bandwidth. The algorithm is developed based on the frame level approach for Versatile video Coding (VVC) and is optimized using the open-source encoder implementation project, VVenC. Specifically, by considering the content characteristic of different videos, the rate-distortion (R-D) curve is refitted using hyperbolic model for the rate control parameters α and β. And the original α and β values of the depth map are modified to better guide the bit allocation. Experimental results indicate that the proposed rate control algorithm outperforms the VVenC 0.3.1.0 frame level rate control algorithm, achieving an average 4.2% BD-rate saving and 1.616dB gain under random access (RA) configuration, which is superior to existing rate control schemes for immersive video. © 2023 SPIE.

关键词： image coding

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Revolutionizing NLP: Multimodal Integration for Enhanced image-to-Text Extraction 3

Revolutionizing NLP: Multimodal Integration for Enhanced Ima...

引用

3rd international conference on Computational Modelling, Simulation and Optimization, ICCMSO 2024

作者： Chiguru, Aparna Rajchandar, K. SR University School of CS & AI Warangal India

ISBN: (纸本)9798350361391

This paper tackles the mixing of picture and written material modalities to enhance natural language processing (NLP), specifically that specializes in picture-to-textual content extraction Our approach combines advanced computer vision techniques and NLP, introducing a multimodal fusion shape that uses Convolutional Neural Networks (CNNs) for image processing and Transformer-primarily based totally models for language statistics. pleasant-grained photograph feature extraction and a move-modal attention mechanism are employed to enhance interpretability and the version's capability to partner visible functions with text. Our approach demonstrates superior performance through benchmark evaluations on specialized datasets, highlighting its effectiveness in achieving enhanced accuracy and efficiency. Beyond theoretical contributions, the research has practical applications in automated image captioning, multimedia content indexing, and accessibility solutions for the visually impaired. This study underscores the synergistic benefits of combining computer vision and NLP techniques, providing a comprehensive understanding of multimodal integration's potential to advance image-to-text extraction in NLP tasks. © 2024 IEEE.

关键词： Convolutional neural networks

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video image Information Mining Algorithms for Badminton on-the-Spot Tactics Analysis 3

Video Image Information Mining Algorithms for Badminton on-t...

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3rd international conference on Smart Data Intelligence, ICSMDI 2023

作者： Li, Haifu Henan Technical Institute P.E. Department Henan Zhengzhou450042 China

ISBN: (纸本)9781665464871

Due to the changes in the camera angle or the working direction of the athlete in the sports video, this method cannot perform an effective regional analysis. Hence, the efficient analysis of images is essential for the action recognition, hence, this paper studies the video image information mining algorithms for badminton on-the-spot tactics analysis. The designed system contains the image segmentation, action recognition and the badminton on-the-spot tactics analysis. To perform image segmentation, the FCM model is considered To perform action recognition, based on the obtained skeleton data, the model is trained by the action label data to classify it. An efficient action representation can capture both static and kinematic information. Then, the system is verified through the real-time data sets. The proposed model is proven to be efficient. © 2023 IEEE.

关键词： image segmentation

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Large Scale image Data processing and Content Recognition Based on Deep Learning 3

Large Scale Image Data Processing and Content Recognition Ba...

引用

3rd international conference on Data Analytics, Computing and Artificial Intelligence, ICDACAI 2024

作者： Wan, Ruoyan Wei, Xiuzhuo Ma, Rui Zhao, Huinan Wu, Feng Changchun Humanities and Sciences College Jilin Changchun130000 China

ISBN: (纸本)9798331519032

As the cornerstone of computer vision (CV), image recognition is of great importance. It not only profoundly affects daily life fields such as facial recognition, intelligent security, and medical image analysis, but also plays a key role in breakthroughs in high-tech fields such as autonomous driving technology, intelligent robots, and industrial inspection. With the vigorous rise of artificial intelligence (AI) technology, especially the rapid development of deep learning (DL) technology, image recognition has ushered in unprecedented changes. This article focuses on the latest applications of DL in the field of image recognition and proposes an innovative large-scale image data processing and content recognition algorithm. This algorithm effectively captures complex features in images by constructing deep neural network models, and continuously optimizes model parameters using massive training data, thereby improving recognition accuracy and significantly enhancing the algorithm's ability to understand image content. The experimental results show that the algorithm exhibits excellent performance in processing large-scale image datasets, with fast recognition speed and industry-leading recognition accuracy, laying a solid foundation for the further application of image recognition technology. © 2024 IEEE.

关键词： Medical robotics

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Application of a Deep Generative Model for Diversified video Subtitles Based on Generative Adversarial Networks 3

Application of a Deep Generative Model for Diversified Video...

引用

3rd Asia-Pacific conference on Communications Technology and Computer Science (ACCTCS)

作者： Shen, Lingzhi Loughborough Univ London London E20 3BS England

ISBN: (纸本)9798350310801

With the continuous development of artificial intelligence, cross-field applications in image recognition, natural language processing, and semantic recognition have gradually emerged. video subtitle generation is one of the typical cross-field application scenarios. By recognizing image semantics and using natural language for generative content construction, users can often understand the content of images intuitively and quickly. In addition, when the contents are displayed in text form, it is convenient for textual retrieval or other text-based image applications. This paper proposes the application of generative adversarial networks in subtitle recognition. By focusing more on generation diversity, the degree of the differentiated description of generated content can be further improved, making image and video subtitles generation content prone to human habits. Specifically, the idea is to use the generative adversarial network to generate the subtitles of the images in the video and use diversified generative models to conduct difference optimization to obtain better generative performance. It is hoped that the research in this paper can help the application of diversified video subtitles generation.

关键词： Generative adversarial network video subtitle generation Deep generative model Natural language processing

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Interactive Segmentation of Art images based on Point Cloud Pre-Training 3

Interactive Segmentation of Art Images based on Point Cloud ...

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3rd international conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Tian, Yuan Tao, Yiran Nanhang Jincheng College Jiangsu Province Nanjing City210000 China

ISBN: (纸本)9798350396157

This study presents an innovative interactive segmentation algorithm for fine art images using point cloud pre-Training principles. With increasing demands for precision and variety in image processing, conventional methods are proving inadequate. image segmentation, a central aspect of visual data manipulation, involves dividing an image into distinct regions based on static or dynamic features. This study reviews supervised and unsupervised segmentation strategies, emphasizing the importance of fuzzy clustering algorithms in practical applications. Despite advances in medical image segmentation, challenges remain due to the complex nature of image processing. A universally applicable segmentation method and standardized evaluation criteria are elusive. To address these challenges, the proposed algorithm combines Local Binary Pattern (LBP) feature extraction with a point cloud pre-Training model, utilizing the U-net architecture for accurate segmentation. Experiments conducted on an Ubuntu 14.04 64-bit OS using C++ and Python demonstrate the effectiveness of the algorithm. The visualized results show its potential for practical applications and lay the foundation for future advances in image segmentation. © 2024 IEEE.

关键词： image segmentation

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