購物比價找書網找車網
FindBook  
 有 1 項符合

Unsupervised Domain Adaptation: Recent Advances and Future Perspectives

的圖書
Unsupervised Domain Adaptation: Recent Advances and Future Perspectives Unsupervised Domain Adaptation: Recent Advances and Future Perspectives

作者:Li 
出版社:Springer
出版日期:2024-04-23
語言:英文   規格:精裝 / 普通級/ 初版
圖書選購
型式價格供應商所屬目錄
 
$ 11999
博客來 博客來
人工智慧
圖書介紹 - 資料來源:博客來   評分:
圖書名稱:Unsupervised Domain Adaptation: Recent Advances and Future Perspectives

內容簡介

Unsupervised domain adaptation (UDA) is a challenging problem in machine learning where the model is trained on a source domain with labeled data and tested on a target domain with unlabeled data. In recent years, UDA has received significant attention from the research community due to its applicability in various real-world scenarios. This book provides a comprehensive review of state-of-the-art UDA methods and explores new variants of UDA that have the potential to advance the field.

The book begins with a clear introduction to the UDA problem and is mainly organized into four technical sections, each focused on a specific piece of UDA research. The first section covers criterion optimization-based UDA, which aims to learn domain-invariant representations by minimizing the discrepancy between source and target domains. The second section discusses bi-classifier adversarial learning-based UDA, which creatively leverages adversarial learning by conducting a minimax game between the feature extractor and two task classifiers. The third section introduces source-free UDA, a novel UDA setting that does not require any raw data from the source domain. The fourth section presents active learning for UDA, which combines domain adaptation and active learning to reduce the amount of labeled data needed for adaptation.

This book is suitable for researchers, graduate students, and practitioners who are interested in UDA and its applications in various fields, primarily in computer vision. The chapters are authored by leading experts in the field and provide a comprehensive and in-depth analysis of the current UDA methods and new directions for future research. With its broad coverage and cutting-edge research, this book is a valuable resource for anyone looking to advance their knowledge of UDA.


 

作者簡介

Jingjing Li is currently a professor with 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 in 2010, 2013, and 2017, respectively. His research interests are in the area of domain adaptation and zero-shot learning. He has co/authored more than 70 peer-reviewed papers, such as IEEE TPAMI, IEEE TIP, IEEE TKDE, CVPR, ICCV, AAAI, IJCAI, and ACM Multimedia. He won Excellent Doctoral Dissertation Award of Chinese Institute of Electronics in 2018.

Lei Zhu is currently a professor with the School of Electronic and Information Engineering, Tongji University. He received his B.Eng. and Ph.D. degrees from Wuhan University of Technology in 2009 and Huazhong University Science and Technology in 2015, respectively. He was a Research Fellow at the University of Queensland (2016-2017). His research interests are in the area of large-scale multimedia content analysis and retrieval. Zhu has co/authored more than 100 peer-reviewed papers, such as ACM SIGIR, ACM MM, IEEE TPAMI, IEEE TIP, IEEE TKDE, and ACM TOIS. His publications have attracted more than 5,600 Google citations. At present, he serves as the Associate Editor of IEEE TBD, ACM TOMM, and Information Sciences. He has served as the Area Chair, Senior Program Committee or reviewer for more than 40 well-known international journals and conferences. He won ACM SIGIR 2019 Best Paper Honorable Mention Award, ADMA 2020 Best Paper Award, ChinaMM 2022 Best Student Paper Award, ACM China SIGMM Rising Star Award, Shandong Provincial Entrepreneurship Award for Returned Students, and Shandong Provincial AI Outstanding Youth Award.

Zhekai Du is currently a third-year Ph.D. student with the School of Computer Science and Engineering, University of Electronic Science and Technology of China (UESTC). His research interests are domain adaptation, domain generalization, and their applications in computer vision. He received his B.Eng. degree from UESTC in 2018. He has co/authored dozens of papers at the top conferences and journals, like CVPR, ACM Multimedia, ECCV, AAAI, and IEEE TPAMI.

 

詳細資料

  • ISBN:9789819710249
  • 規格:精裝 / 普通級 / 初版
  • 出版地:美國
贊助商廣告
 
金石堂 - 今日66折
內部的真相
作者:日影丈吉
出版社:衛城出版
出版日期:2023-03-15
66折: $ 251 
金石堂 - 今日66折
造神:人類探索信仰與宗教的歷史
作者:雷薩.阿斯蘭
出版社:衛城出版
出版日期:2020-09-02
66折: $ 297 
金石堂 - 今日66折
成語就是這樣讀和寫--看成語笑話拚字音字形競賽
作者:呂淑敏
出版社:五南圖書出版股份有限公司
出版日期:2017-03-25
66折: $ 251 
 
Taaze 讀冊生活 - 暢銷排行榜
牽衫尾
作者:葉國居
出版社:聯合文學出版社股份有限公司
出版日期:2024-10-17
$ 270 
金石堂 - 暢銷排行榜
我不會免費跟妳上床(4)
作者:檜原フキ
出版社:台灣角川股份有限公司
出版日期:2024-11-14
$ 111 
金石堂 - 暢銷排行榜
庫洛魔法使 透明牌篇 (首刷限定版) 16(完)
作者:CLAMP
出版社:東立出版社
出版日期:2025-03-31
$ 675 
Taaze 讀冊生活 - 暢銷排行榜
世界上最透明的故事(日本出版界話題作,只有紙本書可以體驗的感動)
作者:杉井光
出版社:皇冠文化出版有限公司
出版日期:2024-09-30
$ 284 
 
金石堂 - 新書排行榜
口罩男子明明不想談戀愛(03)
作者:参号ミツル
出版社:尖端漫畫
出版日期:2024-11-19
$ 119 
Taaze 讀冊生活 - 新書排行榜
滿洲鴉片小隊(05)
作者:門馬司、鹿子
出版社:尖端出版
出版日期:2024-11-20
$ 140 
金石堂 - 新書排行榜
總之就是很可愛(25)
作者:畑健二郎
出版社:尖端漫畫
出版日期:2024-11-21
$ 119 
博客來 - 新書排行榜
生命中最大的寶藏就是你自己Stand by Yourself
作者:曾寶儀
出版社:天下文化
出版日期:2024-10-31
$ 331 
 

©2024 FindBook.com.tw -  購物比價  找書網  找車網  服務條款  隱私權政策