Selective Multiple Classifiers for Weakly Supervised Semantic Segmentation
ABSTRACT Existing weakly supervised semantic segmentation (WSSS) methods based on image‐level labels always rely on class activation maps (CAMs), which measure the relationships between features and classifiers. However, CAMs only focus on the most discriminative regions of images, resulting in thei...
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| Asıl Yazarlar: | , , , |
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| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
Wiley
2025-12-01
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| Seri Bilgileri: | CAAI Transactions on Intelligence Technology |
| Konular: | |
| Online Erişim: | https://doi.org/10.1049/cit2.70042 |
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