The proposed ScoreCAM++ approach enhances the interpretability of deep learning models by modifying the normalization function and incorporating the tanh activation to effectively gate and emphasize the most relevant features in the activation layers.
ConceptLens enhances the interpretability of deep neural networks by visualizing neuron activations and their associated confidence levels through error-margin analysis, providing insights into how these networks make decisions.