Towards Robust Pattern Recognition: A Review | |
Zhang, Xu-Yao1,2; Liu, Cheng-Lin1,2,4; Suen, Ching Y.3 | |
刊名 | PROCEEDINGS OF THE IEEE
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2020-06-01 | |
卷号 | 108期号:6页码:894-922 |
关键词 | Pattern recognition Robustness Task analysis Neural networks Distributed control Big Data Machine intelligence Clean and big data closed world independent and identically distributed robust pattern recognition |
ISSN号 | 0018-9219 |
DOI | 10.1109/JPROC.2020.2989782 |
通讯作者 | Liu, Cheng-Lin(liucl@nlpr.ia.ac.cn) |
英文摘要 | The accuracies for many pattern recognition tasks have increased rapidly year by year, achieving or even outperforming human performance. From the perspective of accuracy, pattern recognition seems to be a nearly solved problem. However, once launched in real applications, the high-accuracy pattern recognition systems may become unstable and unreliable due to the lack of robustness in open and changing environments. In this article, we present a comprehensive review of research toward robust pattern recognition from the perspective of breaking three basic and implicit assumptions: closed-world assumption, independent and identically distributed assumption, and clean and big data assumption, which form the foundation of most pattern recognition models. Actually, our brain is robust at learning concepts continually and incrementally, in complex, open, and changing environments, with different contexts, modalities, and tasks, by showing only a few examples, under weak or noisy supervision. These are the major differences between human intelligence and machine intelligence, which are closely related to the above three assumptions. After witnessing the significant progress in accuracy improvement nowadays, this review paper will enable us to analyze the shortcomings and limitations of current methods and identify future research directions for robust pattern recognition. |
资助项目 | Major Project for New Generation of AI[2018AAA0100400] ; Key Research Program of Frontier Sciences of the Chinese Academy of Sciences (CAS)[ZDBS-LY-7004] ; National Natural Science Foundation of China (NSFC)[61633021] ; National Natural Science Foundation of China (NSFC)[61721004] ; Youth Innovation Promotion Association of CAS[2019141] ; Young Elite Scientists Sponsorship Program of the China Association for Science and Technology (CAST)[2018QNRC001] |
WOS关键词 | NEURAL-NETWORK ; FACE RECOGNITION ; DOMAIN ADAPTATION ; CLASSIFICATION ; SUPPORT ; STYLE ; DIMENSIONALITY ; COMBINATION ; FRAMEWORK ; ALGORITHM |
WOS研究方向 | Engineering |
语种 | 英语 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
WOS记录号 | WOS:000542995400003 |
资助机构 | Major Project for New Generation of AI ; Key Research Program of Frontier Sciences of the Chinese Academy of Sciences (CAS) ; National Natural Science Foundation of China (NSFC) ; Youth Innovation Promotion Association of CAS ; Young Elite Scientists Sponsorship Program of the China Association for Science and Technology (CAST) |
内容类型 | 期刊论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/39948] ![]() |
专题 | 自动化研究所_模式识别国家重点实验室_模式分析与学习团队 |
通讯作者 | Liu, Cheng-Lin |
作者单位 | 1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China 3.Concordia Univ, Ctr Pattern Recognit & Machine Intelligence, Montreal, PQ H3G 1M8, Canada 4.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Xu-Yao,Liu, Cheng-Lin,Suen, Ching Y.. Towards Robust Pattern Recognition: A Review[J]. PROCEEDINGS OF THE IEEE,2020,108(6):894-922. |
APA | Zhang, Xu-Yao,Liu, Cheng-Lin,&Suen, Ching Y..(2020).Towards Robust Pattern Recognition: A Review.PROCEEDINGS OF THE IEEE,108(6),894-922. |
MLA | Zhang, Xu-Yao,et al."Towards Robust Pattern Recognition: A Review".PROCEEDINGS OF THE IEEE 108.6(2020):894-922. |
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