Semi-supervised Segmentation
Semi-Supervised Segmentation is a machine learning approach within image segmentation that leverages a small set of labeled images and a larger set of unlabeled images to train a model, distinguished from fully supervised and unsupervised methods by its joint use of labeled and unlabeled data to improve segmentation accuracy under limited annotation.
663
Publications
41.8K
Citations
2.5K
Authors
740
Institutions
Publications per year
2017–2026
554
663
Fast Online Object Tracking and Segmentation: A Unifying Approach
Qiang Wang, Li Zhang, Luca Bertinetto et al. · 2019 · 1.5K citations
Inf-Net: Automatic COVID-19 Lung Infection Segmentation From CT Images
Deng-Ping Fan, Tao Zhou, Ge-Peng Ji et al. · IEEE Transactions on Medical Imaging · 2020 · 1.2K citations
Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
Xiaokang Chen, Yuhui Yuan, Gang Zeng et al. · 2021 · 1.1K citations
1–5 of 663
2.5K
9
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9
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9
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8
h-index
Inception Institute of Artificial Intelligence, United Arab Emirates
7 publications · 2K citations
7
h-index
1–5 of 2.5K
740

Chinese Academy of Sciences
Beijing, China
23 h-index
108 publications
5.3K citations
Tsinghua University
Beijing, China
19 h-index
41 publications
2.1K citations
Chinese University of Hong Kong
Hong Kong, Hong Kong
18 h-index
61 publications
8K citations
University of Chinese Academy of Sciences
Beijing, China
17 h-index
57 publications
2.2K citations

Shanghai Jiao Tong University
Shanghai, China
14 h-index
28 publications
3.4K citations

University of Hong Kong
Pok Fu Lam, Hong Kong
14 h-index
26 publications
1.5K citations
University of Oxford
Oxford, United Kingdom
13 h-index
26 publications
6.6K citations

Northwestern Polytechnical University
Xi'an, China
12 h-index
35 publications
1.6K citations
1–8 of 740
34 publications · 3.5K citations
28
h-index
Repository · 80 publications · 3.3K citations
28
h-index
22 publications · 2.8K citations
21
h-index
TPAMI · 18 publications · 1.3K citations
17
h-index
15 publications · 1.1K citations
14
h-index
1–5