Review of Fabric Defect Detection using Machine Learning Algorithms

Author(s)	Jenil Dhorajiya, Keyush Shah, Tejas Patil, Prashant Udawant
Country	India
Abstract	This research article focuses on the critical task of fabric defect detection in textile corporations. Fabric defects adversely affect quality and profitability, making their identification crucial. Traditional human visual inspection is inefficient and impractical for mass production due to low detection rates and labor-intensive processes. To overcome these challenges, we propose an alternative approach to enhance efficiency and accuracy in fabric defect detection, ensuring the financial success of textile manufacturers in the face of increasing production complexity.
Keywords	fabric defect detection, object detection, convolutional neural network, prediction
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 5, Issue 5, September-October 2023
Published On	2023-09-17
Cite This	Review of Fabric Defect Detection using Machine Learning Algorithms - Jenil Dhorajiya, Keyush Shah, Tejas Patil, Prashant Udawant - IJFMR Volume 5, Issue 5, September-October 2023. DOI 10.36948/ijfmr.2023.v05i05.5163
DOI	https://doi.org/10.36948/ijfmr.2023.v05i05.5163
Short DOI	https://doi.org/gssfq5

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International Journal For Multidisciplinary Research