Few-class Fidelity: Evaluating Explanations of Real-conditions CNN classifiers with Optimized Perturbations

The wide use of Convolutional Neural Networks (CNN) in numerous domains and real-world classification applications is justified by their high precision and automation speed, helping users concentrate on higher-expertise tasks. To better understand the models and avoid bias during deployment, eXplain