Colour‐patterned fabric defect detection based on an unsupervised multi‐scale U‐shaped denoising convolutional autoencoder model-Reference-Cited by-同舟云学术

Colour‐patterned fabric defect detection based on an unsupervised multi‐scale U‐shaped denoising convolutional autoencoder model

Published:2022-05 Issue:5 Volume:138 Page:522-537
ISSN:1472-3581
Container-title:Coloration Technology
language:en
Short-container-title:Coloration Technology

Author:

Zhang Hongwei¹²,Liu Shuting²,Tan Quanlu²^ORCID,Lu Shuai³,Yao Le¹,Ge Zhiqiang¹

Affiliation:

1. State Key Laboratory of Industrial Control Technology Institute of Industrial Process Control, College of Control Science and Engineering, Zhejiang University Hangzhou China

2. School of Electronics and Information Xi'an Polytechnic University Xi'an China

3. Institute of Engineering Medicine Beijing Institute of Technology Beijing China

Funder

Xi'an Polytechnic University

Innovationsfonden

Natural Science Foundation of Shaanxi Province

Zhejiang University

State Key Laboratory of Industrial Control Technology

National Natural Science Foundation of China

Publisher

Wiley

Subject

Materials Science (miscellaneous),General Chemical Engineering,Chemistry (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/cote.12609

Reference34 articles.

1. Yarn-Dyed Fabric Defect Detection Based On Autocorrelation Function And GLCM

2. Motif-based defect detection for patterned fabric

3. Fabric Defect Detection Using Salience Metric for Color Dissimilarity and Positional Aggregation

4. Deformable Patterned Fabric Defect Detection With Fisher Criterion-Based Deep Learning

5. A universal defect detection approach for various types of fabrics based on the Elo-rating algorithm of the integral image

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