中文版 | English
Title

Unsupervised multilayer fuzzy neural networks for image clustering

Author
Corresponding AuthorIshibuchi,Hisao
Publication Years
2023-04-01
DOI
Source Title
ISSN
0020-0255
Volume622Pages:682-709
Abstract
Currently, labelling a large number of images is still a very challenging task. To tackle the problem of unlabelled data, unsupervised learning has been proposed. Among many unsupervised learning algorithms, K-means is the most popular algorithm. However, in a low-dimensional space, fuzzy c-means, which is more robust and less sensitive to initialization, has several advantages over K-means clustering. On the other hand, stacked convolutional pooling structures and manifold representation play pivotal roles in image clustering. In this paper, we propose an unsupervised multilayer fuzzy neural network for image clustering that unifies fuzzy systems, multilayer convolutional structures and manifold representation. The main contributions are as follows. First, we extend fuzzy systems to unsupervised tasks by introducing manifold representation, which expands the applications of fuzzy systems. Next, we propose the idea of using only a small number of attributes to compute firing strengths. This is implemented to prevent the firing strengths from falling to zero. Finally, randomly generated convolutional weights are used to extract features, which is a good choice for data without labels. It is demonstrated on a wide range of image datasets that the proposed approach is competitive with existing fuzzy and nonfuzzy clustering algorithms.
Keywords
URL[Source Record]
Indexed By
Language
English
SUSTech Authorship
Corresponding
WOS Accession No
WOS:000900836600002
ESI Research Field
COMPUTER SCIENCE
Scopus EID
2-s2.0-85143752296
Data Source
Scopus
Citation statistics
Cited Times [WOS]:2
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/442611
DepartmentDepartment of Computer Science and Engineering
Affiliation
1.School of Software Engineering,Xi'an Jiaotong University,Xi'an,710049,China
2.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
3.Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation,China
4.Institute of Artificial Intelligence and Marine Robotics,College of Marine Electrical Engineering,Dalian Maritime University,Dalian,116026,China
First Author AffilicationDepartment of Computer Science and Engineering
Corresponding Author AffilicationDepartment of Computer Science and Engineering
Recommended Citation
GB/T 7714
Wang,Yifan,Ishibuchi,Hisao,Er,Meng Joo,et al. Unsupervised multilayer fuzzy neural networks for image clustering[J]. INFORMATION SCIENCES,2023,622:682-709.
APA
Wang,Yifan,Ishibuchi,Hisao,Er,Meng Joo,&Zhu,Jihua.(2023).Unsupervised multilayer fuzzy neural networks for image clustering.INFORMATION SCIENCES,622,682-709.
MLA
Wang,Yifan,et al."Unsupervised multilayer fuzzy neural networks for image clustering".INFORMATION SCIENCES 622(2023):682-709.
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