Yarn-dyed fabric defect detection based on an improved autoencoder with Fourier convolution

Compared with solid-colored fabrics, the textures in yarn-dyed fabric images are more complex, making the task of defect detection more challenging. To achieve efficient detection, this study proposes an automatic detection framework for dyed fabric defects. The proposed framework consists of a hard...

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Veröffentlicht in:	Textile research journal Jg. 93; H. 5-6; S. 1153 - 1165
Hauptverfasser:	Xiang, Jun, Pan, Ruru, Gao, Weidong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London, England SAGE Publications 01.03.2023 Sage Publications Ltd
Schlagworte:	Ablation Algorithms Convolution Defects Fabrics Image acquisition Image quality Light sources Training convolution autoencoder yarn-dyed fabric Fourier convolution Defect detection unsupervised learning
ISSN:	0040-5175, 1746-7748
Online-Zugang:	Volltext
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