most citedVisual-TCAV: Concept-based Attribution and Saliency Maps for Post-hoc Explainability in Image Classification

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cs.CV2026★ 1 cited

Visual-TCAV: Concept-based Attribution and Saliency Maps for Post-hoc Explainability in Image Classification

Antonio De Santis, Riccardo Campi, Matteo Bianchi +1

Convolutional Neural Networks (CNNs) have shown remarkable performance in image classification. However, interpreting their predictions is challenging due to the size and complexit…

cs.CV2026

A Framework for Evaluating Zero-Shot Image Generation in Concept-based Explainability

Giacomo Astolfi, Matteo Bianchi, Riccardo Campi +2

Concept-based Explainable Artificial Intelligence (XAI) interprets deep learning models using human-understandable visual features (e.g., textures or object parts) by linking inter…