An inherently interpretable image classifier that selects sparse, semantically meaningful superpixel regions per instance and adaptively determines how many regions to keep based on prediction confidence.
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From Pixels to Perception: Interpretable Predictions via Instance-wise Grouped Feature Selection
An inherently interpretable image classifier that selects sparse, semantically meaningful superpixel regions per instance and adaptively determines how many regions to keep based on prediction confidence.