Fine-Grained Image Analysis: Modern Approaches



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Éditeur :

Springer


Paru le : 2023-07-03



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Description
This book provides a comprehensive overview of the fine-grained image analysis research and modern approaches based on deep learning, spanning the full range of topics needed for designing operational fine-grained image systems. The author begins by providing detailed background information on FGIA, focusing on recognition and retrieval. The author also provides the fundamentals of convolutional neural networks to further make it easier for readers to understand the technical content in the book. The book introduces the main technical paradigms, technological developments, and representative approaches of fine-grained image recognition and fine-grained image retrieval. The author covers multiple popular research topics and includes cross-domain knowledge. The book also highlights advanced applications and topics for future research.  
Pages
206 pages
Collection
n.c
Parution
2023-07-03
Marque
Springer
EAN papier
9783031313738
EAN PDF
9783031313745

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
20
Taille du fichier
7076 Ko
Prix
42,19 €
EAN EPUB
9783031313745

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
20
Taille du fichier
52695 Ko
Prix
42,19 €

Xiu-Shen Wei, Ph.D., is a Professor at Southeast University’s School of Computer Science and Engineering. He received his Ph.D. degree from Nanjing University. Dr. Wei previously served as the Founding Director at Megvii Research Nanjing, Megvii Technology. He was also a visiting Scholar at The University of Adelaide. Dr. Wei’s research interests include deep convolutional neural networks, fine-grained visual analysis, long-tailed distribution learning, general object detection, and weakly supervised learning.

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