A Study to Compare YOLO Family Models for Metal Surface Anomaly Detection-Reference-Cited by-同舟云学术

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A Study to Compare YOLO Family Models for Metal Surface Anomaly Detection

Published:2023-12-15 Issue: Volume:18 Page:5835-5841
ISSN:
Container-title:2023 IEEE International Conference on Big Data (BigData)
language:
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Author:

Koç Abdüsselam¹,Albayrak Özlem¹,Kurt Yaşar²,Ünal Perin³

Affiliation:

1. TED University,Faculty of Computer Engineering,Ankara,Turkey

2. Research & Development TEKNOPAR Industrial Automation, Ostim Technical University Graduation School of Engineering and Sciences,Ankara,Turkey

3. Ostim Technical University,Graduation School of Engineering and Sciences

Funder

Horizon Europe

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10385234/10386078/10386849.pdf?arnumber=10386849

Reference31 articles.

1. YOLO Based Deep Learning Network for Metal Surface Inspection System

2. Method for Determining Treated Metal Surface Quality Using Computer Vision Technology

3. Deep Reinforcement Learning for Anomaly Detection: A Systematic Review

4. Incorporating feedback into tree-based anomaly detection;Das;arXiv preprint arXiv:1708.09441,2017

5. Machine learning algorithms for defect detection in metal laser-based additive manufacturing: A review

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