Fabric Defect Detection Using Activation Layer Embedded Convolutional Neural Network

Wenbin Ouyang; Bugao Xu; Jue Hou; Xiaohui Yuan

doi:10.1109/access.2019.2913620

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JOURNAL ARTICLE

Fabric Defect Detection Using Activation Layer Embedded Convolutional Neural Network

Wenbin Ouyang Bugao Xu Jue Hou Xiaohui Yuan

Year: 2019 Journal: IEEE Access Vol: 7 Pages: 70130-70140 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/access.2019.2913620

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Abstract

This article develops a deep-learning algorithm for an on-loom fabric defect inspection system by combining the techniques of image pre-processing, fabric motif determination, candidate defect map generation, and convolutional neural networks (CNNs).

Keywords:

LOOM Computer science Convolutional neural network Artificial intelligence Segmentation Pattern recognition (psychology) Computer vision Deep learning Pixel Image segmentation Artificial neural network

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0.99

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Topics

Industrial Vision Systems and Defect Detection

Physical Sciences → Engineering → Industrial and Manufacturing Engineering

Optical measurement and interference techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image and Object Detection Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Fabric Defect Detection Using Activation Layer Embedded Convolutional Neural Network

Abstract

Metrics

Citation History

Topics

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