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International Journal of Advanced Research in Computer and Communication Engineering A monthly Peer-reviewed & Refereed journal
ISSN Online 2278-1021ISSN Print 2319-5940Since 2012
IJARCCE adheres to the suggestive parameters outlined by the University Grants Commission (UGC) for peer-reviewed journals, upholding high standards of research quality, ethical publishing, and academic excellence.
← Back to VOLUME 12, ISSUE 3, MARCH 2023

Automated Surface Defect Detection for Industry Products

Nehal Mahajan, Dr. Gobi Natesan

DOI: 10.17148/IJARCCE.2023.12334

Abstract: This research paper provides an overview of the current state of machine learning in surface defect detection for industrial product quality inspection. The study examines traditional machine vision techniques, as well as the latest advancements in deep learning-based approaches. The paper also highlights common challenges faced in the field and presents potential solutions to these challenges. The study concludes with an overview of datasets used for evaluating industrial surface defect detection methods and a comparison of the latest research. This information serves as a valuable reference for future research and development in this field.

Keywords: Surface defect detection, Industrial product quality inspection, Machine vision techniques, Deep learning, Evaluation datasets.

How to Cite:

[1] Nehal Mahajan, Dr. Gobi Natesan, “Automated Surface Defect Detection for Industry Products,” International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2023.12334