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Fine-Grained Image Analysis: Modern Approaches: Synthesis Lectures on Computer Vision

Autor Xiu-Shen Wei
en Limba Engleză Hardback – 4 iul 2023
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.  
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Specificații

ISBN-13: 9783031313738
ISBN-10: 3031313739
Pagini: 206
Ilustrații: XII, 206 p. 90 illus., 86 illus. in color.
Dimensiuni: 168 x 240 mm
Greutate: 0.55 kg
Ediția:2023
Editura: Springer International Publishing
Colecția Springer
Seria Synthesis Lectures on Computer Vision

Locul publicării:Cham, Switzerland

Cuprins

Introduction.- Background.- Benchmark Datasets.- Fine-Grained Image Recognition.- Fine-Grained Image Retrieval.- Resources and Future Work.- Index.

Notă biografică

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.

Textul de pe ultima copertă

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.  

Caracteristici

Provides an essential overview of Fine-Grained Image Analysis that is suitable for students and industry practitioners Covers the main technical paradigms, technological developments, and representative approaches in the area Includes thorough background information, cross-domain knowledge, and advanced applications