模式识别与人工智能
Friday, Apr. 4, 2025 Home      About Journal      Editorial Board      Instructions      Ethics Statement      Contact Us                   中文
Pattern Recognition and Artificial Intelligence  2023, Vol. 36 Issue (12): 1072-1086    DOI: 10.16451/j.cnki.issn1003-6059.202312002
Adapative Perception and Learning of Open-Environment Current Issue| Next Issue| Archive| Adv Search |
Research Advances on Adaptive Perception and Learning in Changing Environment
ZHANG Xuyao1,2, YUAN Xiaotong3, LIU Chenglin1,2
1. State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190;
2. School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049;
3. School of Computer Science, Nanjing University of Information Science and Technology, Nanjing 210044

Download: PDF (822 KB)   HTML (1 KB) 
Export: BibTeX | EndNote (RIS)      
Abstract  The research on artificial intelligence is gradually extended to open environment from closed environment. There are various changing factors in open environment leading to evident performance degradation of the traditional models and learning algorithms based on closed set assumption and independently and identically distributed assumption. Therefore, adaptive perception and learning in changing environments is a frontier topic in the field of artificial intelligence. The latest advances are introduced from three aspects. For category changing, research issues of open set recognition and out-of-distribution detection, new categories discovery and class-incremental learning are introduced. For data distribution changing, issues of domain adaptation, domain generalization and test-time adaptation are introduced. For data quality changing, issues of weakly supervised learning and label noise learning are introduced. Finally, future research trends are analyzed and discussed.
Key wordsKey Words: Changing Environment      Category Set Changing      Data Distribution Changing      Data Quality Changing     
Received: 12 October 2023     
ZTFLH: TP 391  
Fund:Supported by National Key Research and Development Program of China(No.2018AAA0100400); National Natural Science Foundation of China(No.62222609); National Natural Science Foundation of China(No.62076236)
Corresponding Authors: ZHANG Xuyao, Ph.D., professor. His research interests include pattern recognition, machine learning and deep learning.   
About author:: YUAN Xiaotong, Ph.D., professor. His research interests include machine learning, stochastic optimization and computer vision.
LIU Chenglin, Ph.D., professor. His research interests include pattern recognition, machine learning, and document analysis and recognition.
Service
E-mail this article
Add to my bookshelf
Add to citation manager
E-mail Alert
RSS
Articles by authors
ZHANG Xuyao
YUAN Xiaotong
LIU Chenglin
Cite this article:   
ZHANG Xuyao,YUAN Xiaotong,LIU Chenglin. Research Advances on Adaptive Perception and Learning in Changing Environment[J]. Pattern Recognition and Artificial Intelligence, 2023, 36(12): 1072-1086.
URL:  
http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.202312002      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2023/V36/I12/1072
Copyright © 2010 Editorial Office of Pattern Recognition and Artificial Intelligence
Address: No.350 Shushanhu Road, Hefei, Anhui Province, P.R. China Tel: 0551-65591176 Fax:0551-65591176 Email: bjb@iim.ac.cn
Supported by Beijing Magtech  Email:support@magtech.com.cn