Deep Learning in Mining of Visual Content
暫譯: 視覺內容挖掘中的深度學習

Zemmari, Akka, Benois-Pineau, Jenny

Deep Learning in Mining of Visual Content
  • 出版商: Springer
  • 出版日期: 2020-01-23
  • 售價: $2,780
  • 貴賓價: 9.5 折 $2,641
  • 語言: 英文
  • 頁數: 110
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3030343758
  • ISBN-13: 9783030343750
  • 相關分類: DeepLearning

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

This book provides the reader with the fundamental knowledge in the area of deep learning with application to visual content mining. The authors give a fresh view on Deep learning approaches both from the point of view of image understanding and supervised machine learning. It contains chapters which introduce theoretical and mathematical foundations of neural networks and related optimization methods. Then it discusses some particular very popular architectures used in the domain: convolutional neural networks and recurrent neural networks.
Deep Learning is currently at the heart of most cutting edge technologies. It is in the core of the recent advances in Artificial Intelligence. Visual information in Digital form is constantly growing in volume. In such active domains as Computer Vision and Robotics visual information understanding is based on the use of deep learning. Other chapters present applications of deep learning for visual content mining. These include attention mechanisms in deep neural networks and application to digital cultural content mining. An additional application field is also discussed, and illustrates how deep learning can be of very high interest to computer-aided diagnostics of Alzheimer's disease on multimodal imaging.
This book targets advanced-level students studying computer science including computer vision, data analytics and multimedia. Researchers and professionals working in computer science, signal and image processing may also be interested in this book.

商品描述(中文翻譯)

本書為讀者提供了深度學習領域的基本知識，並應用於視覺內容挖掘。作者從圖像理解和監督式機器學習的角度，對深度學習方法提供了全新的見解。書中包含介紹神經網絡及相關優化方法的理論和數學基礎的章節。接著，討論了在該領域中一些特別受歡迎的架構：卷積神經網絡（convolutional neural networks）和遞迴神經網絡（recurrent neural networks）。

深度學習目前是大多數尖端技術的核心。它是近期人工智慧（Artificial Intelligence）進步的核心。數位形式的視覺資訊不斷增長。在計算機視覺（Computer Vision）和機器人技術（Robotics）等活躍領域中，視覺資訊的理解基於深度學習的使用。其他章節介紹了深度學習在視覺內容挖掘中的應用，包括深度神經網絡中的注意力機制（attention mechanisms）及其在數位文化內容挖掘中的應用。還討論了一個額外的應用領域，並說明了深度學習如何對阿茲海默症（Alzheimer's disease）在多模態影像上的電腦輔助診斷具有極高的興趣。

本書針對高級計算機科學學生，包括計算機視覺、數據分析和多媒體領域的學生。從事計算機科學、信號和影像處理的研究人員和專業人士也可能對本書感興趣。

作者簡介

Akka Zemmari has received his Ph.D. degree from the University of Bordeaux 1, France, in 2000. He is an associate professor in computer science since 2001 at University of Bordeaux, France. His research interests include machine and deep learning, randomized algorithms and distributed algorithms and systems.
Jenny Benois-Pineau is a full professor of Computer science at the University Bordeaux and chair of Video Analysis and Indexing research group in Image and Sound Department of LABRI UMR 58000 Université Bordeaux/CNRS/IPB-ENSEIRB. She obtained her PhD degree in Signals and Systems in Moscou and her Habilitation à Diriger la Recherche in Computer Science and Image Processing from University of Nantes, France. Her topics of interest include image and video analysis and indexing, motion analysis and visual content interpretation with machine learning approaches. She is the author and co-author of more than 180 papers in international journals, conference proceedings, book chapters, co-editor of three books. She has tutored an co-tutored 26 PhD students. She is associated editor of EURASIP Signal Processing: Image Communication, Elsevier, Multimedia Tools and applications, Springer, and SPIE Journal of Electronic Imaging journals. She has served on numerous program committees of international conferences of IEEE, ACM and as an expert for international and national research bodies. She is elected IEEE TC IVMSP member for the period of 2018-2020 and is Knight of Academic Palms Order.

作者簡介(中文翻譯)

Akka Zemmari 於2000年獲得法國波爾多大學（University of Bordeaux 1）的博士學位。自2001年以來，他在法國波爾多大學擔任計算機科學副教授。他的研究興趣包括機器學習和深度學習、隨機演算法以及分散式演算法和系統。

Jenny Benois-Pineau 是波爾多大學的計算機科學正教授，並擔任LABRI UMR 58000 Université Bordeaux/CNRS/IPB-ENSEIRB影像與聲音系所的視頻分析與索引研究小組的主席。她在莫斯科獲得信號與系統的博士學位，並在法國南特大學獲得計算機科學與影像處理的研究指導資格（Habilitation à Diriger la Recherche）。她的研究主題包括影像和視頻分析與索引、運動分析以及利用機器學習方法進行視覺內容解釋。她是超過180篇國際期刊、會議論文集和書籍章節的作者和合著者，並擔任三本書的共同編輯。她指導和共同指導了26名博士生。她是《EURASIP Signal Processing: Image Communication》、《Elsevier》、《Multimedia Tools and Applications》、《Springer》和《SPIE Journal of Electronic Imaging》期刊的副編輯。她曾在IEEE、ACM的多個國際會議的程序委員會中任職，並擔任國際和國家研究機構的專家。她於2018-2020年期間當選為IEEE TC IVMSP成員，並獲得學術棕櫚騎士勳章。

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