A project to identify and classify defects on metal surface using Deep Learning. This is a great application of AI for quality control in the manufacturing industry.
Automated defect inspection has been a hot area of research for quality control of industrial products across industries.
This project aims to automatically detect metal surface defects such as rolled-in scale, patches, crazing, pitted surface, inclusion and scratches in Hot-Rolled Steel Strips. The defects are classified into their specific classes via a convolutional neural network (CNN).