MetaCAM as an ensemble-based class activation mapping framework improves model explainability

Abstract The need for clear, trustworthy explanations of deep learning model predictions is essential for high-criticality fields, such as medicine and biometric identification. Class Activation Maps (CAMs) are an increasingly popular category of visual explanation methods for Convolutional Neural N...

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Autors principals:	Kevin Dick, Emily Kaczmarek, Olivier X. Miguel, Alexa C. Bowie, Robin Ducharme, Alysha L. J. Dingwall-Harvey, Steven Hawken, Christine M. Armour, Mark C. Walker
Format:	Artigo
Idioma:	Inglês
Publicat:	Nature Portfolio 2026-03-01
Col·lecció:	Scientific Reports
Matèries:	Class activation map Convolutional neural network Explainable artificial intelligence Ensemble machine learning
Accés en línia:	https://doi.org/10.1038/s41598-026-42879-0
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