Classifier Fusion
Classifier Fusion is a decision-level integration strategy in multimodal machine learning that combines the outputs of multiple individual classifiers to improve overall predictive performance by leveraging complementary information and reducing classifier-specific biases.
4.1K
Publications
263.3K
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13.1K
Authors
3.1K
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Publications per year
2017–2026
1.8K
Parents
4.1K
Robust Real-Time Face Detection
Paul Viola, Michael Jones · International Journal of Computer Vision · 2004 · 14.2K citations
Josef Kittler, M. Hatef, Robert P. W. Duin et al. · IEEE Transactions on Pattern Analysis and Machine Intelligence · 1998 · 5.3K citations
Combining Pattern Classifiers: Methods and Algorithms
Subhash Bagui · Technometrics · 2005 · 3.2K citations
Ensemble based systems in decision making
Robi Polikar · IEEE Circuits and Systems Magazine · 2006 · 2.9K citations
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Chinese Academy of Sciences
Beijing, China
36 h-index
211 publications
10.5K citations
Tsinghua University
Beijing, China
26 h-index
128 publications
5.8K citations
Carnegie Mellon University
Pittsburgh, United States
25 h-index
89 publications
7.9K citations

University of Surrey
Guildford, United Kingdom
25 h-index
88 publications
17.3K citations

Shanghai Jiao Tong University
Shanghai, China
23 h-index
94 publications
5.8K citations

University of Electronic Science and Technology of China
Chengdu, China
23 h-index
75 publications
4.3K citations

Centre National de la Recherche Scientifique
Paris, France
23 h-index
91 publications
5.3K citations
Nanyang Technological University
Singapore, Singapore
22 h-index
69 publications
5K citations
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101 publications · 4.6K citations
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59 publications · 6.5K citations
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TPAMI · 45 publications · 14.6K citations
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48 publications · 4K citations
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47 publications · 5K citations
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