On the Optimum Linear Soft Fusion of Classifiers
We present new analytical developments that contribute to a better understanding of the (soft) fusion of classifiers. To this end, we propose an optimal linear combiner based on a minimum mean-square-error class estimation approach. This solution allows us to define a post-fusion mean-square-error i...
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| 主要な著者: | , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
MDPI AG
2025-05-01
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| シリーズ: | Applied Sciences |
| 主題: | |
| オンライン･アクセス: | https://www.mdpi.com/2076-3417/15/9/5038 |
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