Contrastive Gradient-Flow Interpretation (CGFI): A Composable Operator for Class-Discriminative Explanation of Convolutional Neural Networks
Growing deployment of Convolutional Neural Networks in safety-critical domains has intensified the need for transparent, discriminative explanations, yet gradient-based methods such as Grad-CAM compute explanations for a single class score, producing saliency maps that activate regions shared with competing alternative...