Facial Kinship Verification / SpringerBriefs in Computer Science (PDF)
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This book provides the first systematic study of facial kinship verification, a new research topic in biometrics. It presents three key aspects of facial kinship verification: 1) feature learning for kinship verification, 2) metric learning for kinship verification, and 3) video-based kinship verification, and reviews state-of-the-art research findings on facial kinship verification.
Many of the feature-learning and metric-learning methods presented in this book can also be easily applied for other face analysis tasks, e.g., face recognition, facial expression recognition, facial age estimation and gender classification. Further, it is a valuable resource for researchers working on other computer vision and pattern recognition topics such as feature-learning-based and metric-learning-based visual analysis.
Dr. Jiwen Lu received his B.Eng. degree in mechanical engineering and M.Eng. degree in electrical engineering from the Xi'an University of Technology, Xi'an, China, and his Ph.D. degree in electrical engineering from the Nanyang Technological University, Singapore, in 2003, 2006, and 2012, respectively. He is currently an associate professor at the Department of Automation, Tsinghua University, Beijing, China. From March 2011 to November 2015, he was a research scientist at the Advanced Digital Sciences Center, Singapore. His research interests include computer vision, pattern recognition, and machine learning. He has authored/co-authored over 140 scientific papers in these areas, 38 of which were IEEE Transactions papers. He serves/has served as an associate editor of Pattern Recognition Letters, Neurocomputing, and IEEE Access; a managing guest editor of Pattern Recognition and Image and Vision Computing, a guest editor of Computer Vision and Image Understanding, and an elected member of the Information Forensics and Security Technical Committee of the IEEE Signal Processing Society. He
- Autoren: Haibin Yan , Jiwen Lu
- 2017, 1st ed. 2017, 82 Seiten, Englisch
- Verlag: Springer-Verlag GmbH
- ISBN-10: 9811044848
- ISBN-13: 9789811044847
- Erscheinungsdatum: 31.05.2017
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