Development of Design and Evaluation Tool for CNN, CAE and SVM - Visualization and location estimation of defective parts of industrial products Using CAE -

Abstract

The authors have been developing a design and training application with a user-friendly operation interface for CNN (Convolutional Neural Network), CAE (Convolutional Auto Encoder) and SVM (Support Vector Machine), which can be used for the defect detection of various types of industrial products even without deep skills and knowledges concerning information technology. The application is required to have a visualization ability of small defects which would be the causes of classification results, however, it seems to be not easy to provide such a promising function as clearly identifying the position of defect. In this presentation, CAE is applied to the visualization and position detection of such small defects included in images of industrial products. The effectiveness and promise are evaluated through visualization experiments of defect areas included in test images.