Fig. 1
From: A novel dual-student reverse knowledge distillation method for magnetic tile defect detection
Overview of the dual-student reverse knowledge distillation framework: Our model leverages a pre-trained teacher encoder as a feature extractor. The struct student focuses on the efficient integration and reconstruction of multi-level features, while the detail student enhances the handling of fine-grained, gradient, and irregular texture variations.
