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cs.CV2026
SaliencyDecor: Enhancing Neural Network Interpretability through Feature Decorrelation
Ali Karkehabadi, Jamshid Hassanpour, Houman Homayoun +1
Gradient-based saliency methods are widely used to interpret deep neural networks, yet they often produce noisy and unstable explanations that poorly align with semantically meanin…
cs.CV2024
Overcoming Dimensional Collapse in Self-supervised Contrastive Learning for Medical Image Segmentation
Jamshid Hassanpour, Vinkle Srivastav, Didier Mutter +1
Self-supervised learning (SSL) approaches have achieved great success when the amount of labeled data is limited. Within SSL, models learn robust feature representations by solving…