Image Classification for Manufacturing Defects

Build a computer vision model that identifies manufacturing defects in electronic component photographs from assembly line cameras. The model must classify defects into 8 categories (scratch, crack, dent, discoloration, missing_pin, solder_bridge, correct, unknown) with at least 95% accuracy. Must be deployable on edge devices with < 50MB model size and run inference under 100ms per image on CPU.