“Visual interpretability: saliency maps and interpretable classification”
During this INT/CONECT seminar, Pr Ronan Sicre will present his recent work on “Visual interpretability: saliency maps and interpretable classification.”
Abstract : We will first review previous work on visual interpretability methods and particularly saliency-based methods. We will then present Opti-CAM, a CAM-based method that optimizes a masking objective per instance. The resulting saliency map highlights the important area of an image regarding the decision of a trained image classification network. Then, we will review some works around interpretable image classification using parts or prototype-based architectures.