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Titlebook: Innovations in Computational Intelligence and Computer Vision; Proceedings of ICICV Satyabrata Roy,Deepak Sinwar,Jo?o Manuel R. S. Tav Conf

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書目名稱Innovations in Computational Intelligence and Computer Vision
副標題Proceedings of ICICV
編輯Satyabrata Roy,Deepak Sinwar,Jo?o Manuel R. S. Tav
視頻videohttp://file.papertrans.cn/468/467059/467059.mp4
概述Presents research works in the field of computational intelligence and computer vision.Provides original works presented at ICICV 2022 held in Jaipur, India.Serves as a reference for researchers and p
叢書名稱Lecture Notes in Networks and Systems
圖書封面Titlebook: Innovations in Computational Intelligence and Computer Vision; Proceedings of ICICV Satyabrata Roy,Deepak Sinwar,Jo?o Manuel R. S. Tav Conf
描述This book presents high-quality, peer-reviewed papers from the International Conference on “Innovations in Computational Intelligence and Computer Vision (ICICV 2022),” hosted by Manipal University Jaipur, Rajasthan, India, on 24–25 November 2022. The book includes a collection of innovative ideas from researchers, scientists, academics, industry professionals and students. The book covers a variety of topics, such as artificial intelligence and computer vision, image processing and video analysis, applications and services of artificial intelligence and computer vision, interdisciplinary areas combining artificial intelligence and computer vision, and other innovative practices..
出版日期Conference proceedings 2023
關鍵詞Artificial Intelligence; Computer Vision; Image Processing; Video Analysis; Innovative Practices; ICICV 2
版次1
doihttps://doi.org/10.1007/978-981-99-2602-2
isbn_softcover978-981-99-2601-5
isbn_ebook978-981-99-2602-2Series ISSN 2367-3370 Series E-ISSN 2367-3389
issn_series 2367-3370
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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Innovations in Computational Intelligence and Computer Vision978-981-99-2602-2Series ISSN 2367-3370 Series E-ISSN 2367-3389
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Integrating ResNet18 and YOLOv4 for Pedestrian Detection,ion tasks, pedestrian detection has been the most challenging. The scope and use of pedestrian detection task in surveillance, traffic monitoring, and autonomous cars like The Tesla’s of the world makes it an essential field of research. To this cause, the work done by the YOLO detection algorithms
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