Automated Surface Defect Inspection Based on Autoencoders and Fully Convolutional Neural Networks

Automated Surface Defect Inspection Based on Autoencoders and Fully Convolutional Neural Networks

This study aims to develop a novel automated computer vision algorithm for quality inspection of surfaces with complex patterns. The proposed algorithm is based on both an autoencoder (AE) and a fully convolutional neural network (FCN). The AE is adopted for the self-generation of templates from tes...

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Bibliographic Details
Main Authors: Cheng-Wei Lei, Li Zhang, Tsung-Ming Tai, Chen-Chieh Tsai, Wen-Jyi Hwang, Yun-Jie Jhang
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Applied Sciences
Subjects:
surface inspection
defect detection
artificial intelligence
autoencoder
convolutional neural networks
Online Access:https://www.mdpi.com/2076-3417/11/17/7838

Internet

https://www.mdpi.com/2076-3417/11/17/7838

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