Unsupervised Image Classification
Unsupervised Image Classification is a method in computer vision that assigns labels to images based on learned patterns without prior annotation, distinguishing itself from supervised approaches by relying solely on intrinsic data structures to infer class boundaries.
468
Publications
29K
Citations
1.5K
Authors
637
Institutions
Publications per year
2017–2026
141
Parents
468
1–5 of 468
1.5K
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637

Chinese Academy of Sciences
Beijing, China
14 h-index
55 publications
2.1K citations
Wuhan University
Wuhan, China
13 h-index
49 publications
3.3K citations

Centre National de la Recherche Scientifique
Paris, France
13 h-index
34 publications
1.7K citations
State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing
Wuhan, China
9 h-index
26 publications
2.5K citations
University of Chinese Academy of Sciences
Beijing, China
7 h-index
15 publications
599 citations
Tsinghua University
Beijing, China
7 h-index
24 publications
969 citations
California Institute of Technology
Pasadena, United States
7 h-index
10 publications
3.1K citations
Institut national de recherche en sciences et technologies du numérique
Le Chesnay-Rocquencourt, France
6 h-index
13 publications
572 citations
1–8 of 637
41 publications · 3.3K citations
27
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27 publications · 3.8K citations
24
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Repository · 17 publications · 620 citations
14
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GRSL · 12 publications · 385 citations
11
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11 publications · 466 citations
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