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Robust feature knowledge distillation for enhanced performance of lightweight crack segmentation models
RFKD distils knowledge from a teacher model's logit layers and intermediate feature maps while leveraging mixed clean and noisy images to transfer robust patterns to the student model, improving its precision, generalisation, and anti-noise performance.
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