Entropy-Regularized Attention for Explainable Histological Classification with Convolutional and Hybrid Models
Deep learning models such as convolutional neural networks (CNNs) and vision transformers (ViTs) perform well in histological image classification, but often lack interpretability. We introduce a unified framework that adds an attention branch and CAM Fostering, an entropy-based regularizer, to impr...
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| Main Authors: | Pedro L. Miguel, Leandro A. Neves, Alessandra Lumini, Giuliano C. Medalha, Guilherme F. Roberto, Guilherme B. Rozendo, Adriano M. Cansian, Thaína A. A. Tosta, Marcelo Z. do Nascimento |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/27/7/722 |
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