{"product_id":"pattern-recognition-and-computer-vision-5th-chinese-conference-prcv-2022-shenzhen-china-november-47-2022-proceedings-part-iii-9783031189128","title":"Pattern Recognition and Computer Vision: 5th Chinese Conference, PRCV 2022, Shenzhen, China, November 4-7, 2022, Proceedings, Part III","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003eThe 4-volume set LNCS 13534,13535,13536 and 13537 contains the refereed proceedings of the 5th Chinese Conference on Pattern Recognition and Computer Vision,PRCV 2022, with 233 full papers organized in various topical sections. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 775 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 13 October 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Springer International Publishing AG\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThe 5th Chinese Conference on Pattern Recognition and Computer Vision (PRCV 2022) was held in Shenzhen, China, in November 2022, and its proceedings have been published in a four-volume set, LNCS 13534, 13535, 13536, and 13537. The conference received a total of 564 submissions, from which 233 full papers were selected for inclusion in the proceedings. These papers were organized into seven topical sections:\u003cbr\u003e\u003cbr\u003eTheories and Feature Extraction: This section covered various theories and techniques related to pattern recognition and computer vision, including feature extraction, dimensionality reduction, and pattern classification.\u003cbr\u003e\u003cbr\u003eMachine learning, Multimedia and Multimodal: This section explored the application of machine learning and deep learning to multimedia and multimodal data, such as images, videos, and audio. It also covered topics such as video analysis, facial recognition, and speech recognition.\u003cbr\u003e\u003cbr\u003eOptimization and Neural Network and Deep Learning: This section focused on optimization algorithms, neural network architectures, and deep learning techniques for solving pattern recognition and computer vision problems. It covered topics such as neural network training, regularization, and transfer learning.\u003cbr\u003e\u003cbr\u003eBiomedical Image Processing and Analysis: This section covered the application of pattern recognition and computer vision to biomedical imaging, including medical image segmentation, diagnosis, and treatment planning. It also included topics such as image registration, histogram equalization, and texture analysis.\u003cbr\u003e\u003cbr\u003ePattern Classification and Clustering: This section addressed the classification and clustering of patterns in various domains, such as image, video, and text. It covered topics such as supervised learning, unsupervised learning, and clustering algorithms.\u003cbr\u003e\u003cbr\u003eThree-Dimensional Computer Vision and Reconstruction: This section explored the techniques and applications of three-dimensional computer vision, including 3D object detection, reconstruction, and modeling. It also covered topics such as point cloud processing and volumetric rendering.\u003cbr\u003e\u003cbr\u003eRobots and Autonomous Driving: This section covered the development of robots and autonomous systems for various applications, including navigation, surveillance, and industrial automation. It also included topics such as robot vision, motion planning, and control.\u003cbr\u003e\u003cbr\u003eRecognition, Remote Sensing, and Vision Analysis and Understanding: This section covered the recognition of objects, scenes, and faces in images and videos using machine learning and deep learning techniques. It also included topics such as image segmentation, object tracking, and scene understanding.\u003cbr\u003e\u003cbr\u003eImage Processing and Low-level Vision: This section covered the processing and analysis of images at the low-level, including image enhancement, restoration, and compression. It also included topics such as image segmentation, feature extraction, and pattern recognition.\u003cbr\u003e\u003cbr\u003eObject Detection, Segmentation, and Tracking: This section addressed the detection, segmentation, and tracking of objects in images and videos using machine learning and deep learning techniques. It also covered topics such as object pose estimation, object recognition, and scene understanding.\u003cbr\u003e\u003cbr\u003eIn conclusion, the 5th Chinese Conference on Pattern Recognition and Computer Vision (PRCV 2022) was a highly successful event that brought together researchers from around the world to share their latest findings and advancements in the field. The proceedings of the conference, published in LNCS 13534, 13535, 13536, and 13537, represent a significant contribution to the literature on pattern recognition and computer vision and will be of great value to researchers, practitioners, and students in this field.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 1199g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 235 x 155 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9783031189128\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 1st ed. 2022\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Paperback \/ softback","offer_id":44270942552314,"sku":"9783031189128","price":38.42,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/noImage_1_19eca9a1-07f9-4d9b-8127-9153474aa764.jpg?v=1686154444","url":"https:\/\/shulphink.com\/products\/pattern-recognition-and-computer-vision-5th-chinese-conference-prcv-2022-shenzhen-china-november-47-2022-proceedings-part-iii-9783031189128","provider":"Shulph Ink","version":"1.0","type":"link"}