Multi-Modal Hash Learning: Efficient Multimedia Retrieval and Recommendations

Zhu, Lei, Li, Jingjing, Guan, Weili

Multi-Modal Hash Learning: Efficient Multimedia Retrieval and Recommendations
  • 出版商: Springer
  • 出版日期: 2024-08-23
  • 售價: $1,840
  • 貴賓價: 9.5 折 $1,748
  • 語言: 英文
  • 頁數: 199
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 303137293X
  • ISBN-13: 9783031372933

    • 海外代購書籍(需單獨結帳)

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商品描述

This book systemically presents key concepts of multi-modal hashing technology, recent advances on large-scale efficient multimedia search and recommendation, and recent achievements in multimedia indexing technology. With the explosive growth of multimedia contents, multimedia retrieval is currently facing unprecedented challenges in both storage cost and retrieval speed. The multi-modal hashing technique can project high-dimensional data into compact binary hash codes. With it, the most time-consuming semantic similarity computation during the multimedia retrieval process can be significantly accelerated with fast Hamming distance computation, and meanwhile the storage cost can be reduced greatly by the binary embedding. The authors introduce the categorization of existing multi-modal hashing methods according to various metrics and datasets. The authors also collect recent multi-modal hashing techniques and describe the motivation, objective formulations, and optimization steps for context-aware hashing methods based on the tag-semantics transfer.


商品描述(中文翻譯)

本書系統性地介紹了多模態哈希技術的關鍵概念、在大規模高效多媒體搜索和推薦方面的最新進展，以及多媒體索引技術的最新成就。隨著多媒體內容的爆炸性增長，多媒體檢索目前在存儲成本和檢索速度上面臨前所未有的挑戰。多模態哈希技術可以將高維數據投影為緊湊的二進位哈希碼。藉此，在多媒體檢索過程中最耗時的語義相似度計算可以通過快速的漢明距離計算顯著加速，同時存儲成本也可以通過二進位嵌入大幅降低。作者根據各種指標和數據集介紹了現有多模態哈希方法的分類。作者還收集了近期的多模態哈希技術，並描述了基於標籤語義轉移的上下文感知哈希方法的動機、目標公式和優化步驟。

作者簡介

Lei Zhu, Ph.D. is a Professor in the School of Information Science and Engineering, Shandong Normal University. He received his B.Eng. and Ph.D. degrees from Wuhan University of Technology and Huazhong University Science and Technology, respectively. He was a Research Fellow at the University of Queensland (2016-2017). His research interests include large-scale multimedia content analysis and retrieval.

Jingjing Li, Ph.D, is a Professor in the School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC). He received his B.Eng., M.Sc. and Ph.D. degrees from UESTC. His research interests include domain adaptation and zero-shot learning.

Weili Guan received a master degree from National University of Singapore. After that, she joined Hewlett Packard Enterprise in Singapore as a Software Engineer and worked there for several years. She is currently a PhD student with the Faculty of Information Technology, Monash University (Clayton Campus), Australia. Her research interests are multimedia computing and information retrieval. She has authored or co-authored more than 30 papers at first-tier conferences and journals, such as ACM MM, SIGIR, and IEEE TIP.

作者簡介(中文翻譯)

雷珠博士是山東師範大學資訊科學與工程學院的教授。他分別在武漢理工大學和華中科技大學獲得工程學學士和博士學位。他曾於2016年至2017年擔任昆士蘭大學的研究員。他的研究興趣包括大規模多媒體內容分析與檢索。

李晶晶博士是中國電子科技大學計算機科學與工程學院的教授。他在中國電子科技大學獲得工程學學士、碩士及博士學位。他的研究興趣包括領域適應和零樣本學習。

關偉莉在新加坡國立大學獲得碩士學位。之後，她在新加坡的惠普企業擔任軟體工程師，並在那裡工作了幾年。她目前是澳大利亞莫納什大學（克萊頓校區）資訊科技學院的博士生。她的研究興趣為多媒體計算和資訊檢索。她已在ACM MM、SIGIR和IEEE TIP等一流會議和期刊上發表或共同發表超過30篇論文。

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