Fine-Grained Image Analysis: Modern Approaches

Wei, Xiu-Shen

Fine-Grained Image Analysis: Modern Approaches
  • 出版商: Springer
  • 出版日期: 2023-07-04
  • 售價: $1,940
  • 貴賓價: 9.5 折 $1,843
  • 語言: 英文
  • 頁數: 206
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031313739
  • ISBN-13: 9783031313738

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

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.

商品描述(中文翻譯)

本書提供了對細粒度圖像分析研究和基於深度學習的現代方法的全面概述，涵蓋了設計操作性細粒度圖像系統所需的所有主題。作者首先提供了關於細粒度圖像分析的詳細背景信息，重點放在識別和檢索上。作者還介紹了卷積神經網絡的基礎知識，以便讓讀者更容易理解書中的技術內容。本書介紹了細粒度圖像識別和細粒度圖像檢索的主要技術範例、技術發展和代表性方法。作者涵蓋了多個熱門研究主題，並包含跨領域知識。本書還突出了未來研究的高級應用和主題。

作者簡介

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.

作者簡介(中文翻譯)

魏秀慎博士是東南大學計算機科學與工程學院的教授。他在南京大學獲得了博士學位。魏博士曾擔任過旷視科技南京研究院的創始主任，也曾在阿德萊德大學擔任訪問學者。魏博士的研究興趣包括深度卷積神經網絡、細粒度視覺分析、長尾分佈學習、通用物體檢測和弱監督學習。

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