{"product_id":"computer-vision-accv-2022-workshops-16th-asian-conference-on-computer-vision-macao-china-december-48-2022-revised-selected-papers-9783031270659","title":"Computer Vision - ACCV 2022 Workshops: 16th Asian Conference on Computer Vision, Macao, China, December 4-8, 2022, Revised Selected Papers","description":"\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eThis book presents the refereed post-conference proceedings of the workshops held at the 16th Asian Conference on Computer Vision,ACCV 2022, covering various topics in computer vision, including learning with limited data, adversarial machine learning, medical computing, visual semantic analysis, vision transformers, and deep learning-based small object detection. \u003c\/blockquote\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 378 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 09 March 2023\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer International Publishing AG\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003eThe 16th Asian Conference on Computer Vision (ACCV) 2022, held in Macao, China, in December 2022, saw the convening of a series of workshops that brought together experts from various fields to explore cutting-edge advancements in computer vision. This remarkable collection of refereed post-conference proceedings, compiled in this book, showcases the latest research and developments in the field.\u003cbr\u003e\u003cbr\u003eSpanning a wide range of topics, the 25 papers included in this volume were meticulously reviewed and selected from a pool of 40 submissions. These papers have been thoughtfully organized into topical sections, allowing readers to delve into the intricacies of various aspects of computer vision.\u003cbr\u003e\u003cbr\u003eThe first section, titled \"Learning with Limited Data for Face Analysis,\" delves into the challenges of analyzing faces with limited data, exploring techniques such as transfer learning, generative adversarial networks, and deep learning-based face recognition. This section highlights the potential of these methods in addressing real-world applications, such as face identification and emotion recognition.\u003cbr\u003e\u003cbr\u003eThe second section, titled \"Adversarial Machine Learning Towards Advanced Vision Systems,\" explores the use of adversarial learning in developing robust and accurate vision systems. This section discusses the role of adversarial examples in detecting and mitigating adversarial attacks, as well as the application of adversarial learning in tasks such as object detection, image segmentation, and facial recognition.\u003cbr\u003e\u003cbr\u003eThe third section, titled \"Computer Vision for Medical Computing,\" focuses on the application of computer vision in healthcare and medical imaging. This section explores the use of computer vision in diagnosing diseases, analyzing medical images, and developing personalized treatment plans. It highlights the potential of computer vision to improve patient care and outcomes.\u003cbr\u003e\u003cbr\u003eThe fourth section, titled \"Machine Learning and Computing for Visual Semantic Analysis,\" explores the use of machine learning and computing techniques to understand and interpret visual content. This section discusses the application of deep learning in image recognition, scene understanding, and object detection, as well as the use of graph networks and convolutional neural networks for visual semantic analysis.\u003cbr\u003e\u003cbr\u003eThe fifth section, titled \"Vision Transformers Theory and Applications,\" delves into the theory and applications of vision transformers, a powerful class of neural network architectures. This section discusses the architecture of vision transformers, their training and optimization techniques, and their applications in tasks such as image restoration, object detection, and facial recognition.\u003cbr\u003e\u003cbr\u003eThe final section, titled \"Deep Learning-Based Small Object Detection from Images and Videos,\" focuses on the use of deep learning for small object detection in images and videos. This section explores the use of convolutional neural networks, recurrent neural networks, and transfer learning techniques to detect and classify small objects in complex scenes.\u003cbr\u003e\u003cbr\u003eIn conclusion, this book serves as a valuable resource for researchers, practitioners, and students in the field of computer vision. It provides a comprehensive overview of the latest advancements in computer vision, covering a wide range of topics and highlighting the potential of these technologies to revolutionize various industries. The contributions of the authors and reviewers in putting together this exceptional collection are highly commendable, and it is expected to inspire further research and development in the years to come.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 599g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783031270659\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2023\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44272378315002,"sku":"9783031270659","price":55.5,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_8111eec8-ebd1-4a3e-932c-0252f70127a8.jpg?v=1686252784","url":"https:\/\/shulphink.com\/products\/computer-vision-accv-2022-workshops-16th-asian-conference-on-computer-vision-macao-china-december-48-2022-revised-selected-papers-9783031270659","provider":"Shulph Ink","version":"1.0","type":"link"}