Lightweight Corrosion Image Classification via Self-Training and Progressive Knowledge Distillation
A class-aware proportional screening strategy that expands a small, labelled dataset with 19,964 unlabeled images to create a more balanced training set and minimizes computational overhead without sacrificing accuracy, thereby offering a practical solution for real-world monitoring on resource-constrained devices.