AINeutralarXiv – CS AI · Jun 106/10
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Visual-TCAV: Concept-based Attribution and Saliency Maps for Post-hoc Explainability in Image Classification
Researchers introduce Visual-TCAV, a novel explainability framework for image classification that combines concept-based and saliency-based methods to provide both local and global interpretations of CNN predictions. The method demonstrates improved faithfulness compared to existing approaches like TCAV, bridging a gap between understanding where networks recognize concepts and how those concepts contribute to specific predictions.