Inspection of metal parts based on CNN using YOLO Network.

Abstract

The machine vision is a latest approach which provides automation in inspection of systems. Automatic inspection using machine learning and Convolutional Neural Network (CNN) is a popular trend for detection of metal parts on automobile infrastructure in order to speed up the process and improve accuracy of results. Deep CNN are able to perform both the feature extraction and classification.  This proposed model is used to detect, label and classify metal parts and inspect them based on image analytics using deep learning. This is used to eliminate manual errors and provide better, fast and accurate result.