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Titlebook: Computer Vision and Image Processing; 5th International Co Satish Kumar Singh,Partha Roy,P. Nagabhushan Conference proceedings 2021 The Edi

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書目名稱Computer Vision and Image Processing
副標(biāo)題5th International Co
編輯Satish Kumar Singh,Partha Roy,P. Nagabhushan
視頻videohttp://file.papertrans.cn/235/234056/234056.mp4
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: Computer Vision and Image Processing; 5th International Co Satish Kumar Singh,Partha Roy,P. Nagabhushan Conference proceedings 2021 The Edi
描述This three-volume set (CCIS 1367-1368)?constitutes the refereed proceedings of the?5th International Conference on?Computer Vision and Image Processing, CVIP 2020, held in Prayagraj, India, in?December?2020. Due to the COVID-19 pandemic the conference was partially held online.?.The 134 papers papers were carefully reviewed and selected from 352 submissions. The papers present recent research on?such topics?as biometrics, forensics, content protection, image enhancement/super-resolution/restoration, motion and tracking, image or video retrieval, image, image/video processing for autonomous vehicles, video scene understanding, human-computer interaction, document image analysis, face, iris, emotion, sign language and gesture recognition, 3D image/video processing, action and event detection/recognition, medical image and video analysis, vision-based human GAIT analysis, remote sensing, and more..
出版日期Conference proceedings 2021
關(guān)鍵詞artificial intelligence; computer hardware; computer networks; computer systems; computer vision; deep le
版次1
doihttps://doi.org/10.1007/978-981-16-1103-2
isbn_softcover978-981-16-1102-5
isbn_ebook978-981-16-1103-2Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Eelco Plugge,Peter Membrey,Tim Hawkinsd concept is generic and can be used with any existing loss function. We test the Hard-Mining loss with different losses such as Cross-Entropy, Angular-Softmax and ArcFace. The proposed Hard-Mining loss is tested over widely used Labeled Faces in the Wild (LFW) and YouTube Faces (YTF) datasets. The
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