A New Subspace Clustering Strategy for AI-Based Data Analysis in IoT System
Cui, Zhihua1; Jing, Xuechun1; Zhao, Peng1; Zhang, Wensheng2; Chen, Jinjun3
发表期刊IEEE INTERNET OF THINGS JOURNAL
ISSN2327-4662
2021-08-15
卷号8期号:16页码:12540-12549
通讯作者Cui, Zhihua(cuizhihua@tyust.edu.cn)
摘要The Internet-of-Things (IoT) technology is widely used in various fields. In the Earth observation system, hyperspectral images (HSIs) are acquired by hyperspectral sensors and always transmitted to the cloud for analysis. In order to reduce cost and reply promptly, we deploy artificial intelligence (AI) models for data analysis on edge servers. Subspace clustering, the core of the AI model, is employed to analyze high-dimensional image data such as HSIs. However, most traditional subspace clustering algorithms construct a single model, which can be affected by noise more easily. It hardly balances the sparsity and connectivity of the representation coefficient matrix. Therefore, we proposed a postprocess strategy of subspace clustering for taking account of sparsity and connectivity. First, we define close neighbors as having more common neighbors and higher coefficients neighbors, where the close neighbors are selected according to the nondominated sorting algorithm. Second, the coefficients between the sample and close neighbors are reserved, incorrect, or useless connections are pruned. Then, the postprocess strategy can reserve the intrasubspace connection and prune the intersubspace connection. In experiments, we verified the universality and effectiveness of postprocessing strategies in the traditional image recognition field and IoT field, respectively. The experiment results demonstrate that the proposed strategy can process noise data in the IoT to improve clustering accuracy.
关键词Sparse matrices Internet of Things Clustering algorithms Correlation Artificial intelligence Servers Hyperspectral imaging Close neighbors data analysis hyperspectral images (HSIs) Internet of Things (IoT) subspace clustering
DOI10.1109/JIOT.2021.3056578
关键词[WOS]ALGORITHM ; SEGMENTATION ; INTERNET ; ROBUST
收录类别SCI
语种英语
资助项目National Key Research and Development Program of China[2018 YFC1604000] ; National Natural Science Foundation of China[61806138] ; National Natural Science Foundation of China[61772478] ; National Natural Science Foundation of China[U1636220] ; National Natural Science Foundation of China[61961160707] ; National Natural Science Foundation of China[61976212] ; Key Research and Development Program of Shanxi Province (International Cooperation)[201903D421048] ; Australian Research Council (ARC)[DP190101893] ; Australian Research Council (ARC)[DP170100136] ; Australian Research Council (ARC)[LP180100758]
项目资助者National Key Research and Development Program of China ; National Natural Science Foundation of China ; Key Research and Development Program of Shanxi Province (International Cooperation) ; Australian Research Council (ARC)
WOS研究方向Computer Science ; Engineering ; Telecommunications
WOS类目Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS记录号WOS:000682147600012
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
被引频次:147[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/45698
专题多模态人工智能系统全国重点实验室_人工智能与机器学习(杨雪冰)-技术团队
通讯作者Cui, Zhihua
作者单位1.Taiyuan Univ Sci & Technol, Sch Comp Sci & Technol, Taiyuan 030024, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Intelligent Control & Management Co, Beijing 100190, Peoples R China
3.Swinburne Univ Technol, Dept Comp Sci & Software Engn, Melbourne, Vic 3000, Australia
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GB/T 7714
Cui, Zhihua,Jing, Xuechun,Zhao, Peng,et al. A New Subspace Clustering Strategy for AI-Based Data Analysis in IoT System[J]. IEEE INTERNET OF THINGS JOURNAL,2021,8(16):12540-12549.
APA Cui, Zhihua,Jing, Xuechun,Zhao, Peng,Zhang, Wensheng,&Chen, Jinjun.(2021).A New Subspace Clustering Strategy for AI-Based Data Analysis in IoT System.IEEE INTERNET OF THINGS JOURNAL,8(16),12540-12549.
MLA Cui, Zhihua,et al."A New Subspace Clustering Strategy for AI-Based Data Analysis in IoT System".IEEE INTERNET OF THINGS JOURNAL 8.16(2021):12540-12549.
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