<b>Construction of Defect Detection System for Image Data</b><b>Using Machine Learning and Image Processing</b>-Reference-Cited by-同舟云学术

Construction of Defect Detection System for Image DataUsing Machine Learning and Image Processing

Published:2017 Issue:2 Volume:3 Page:46-58
ISSN:2189-3195
Container-title:Total Quality Science
language:en
Short-container-title:TQS

Author:

YOSHIDA Kenta¹,IWASAWA Tatsuya¹,SANO Natsuki²,TANAKA Mirai³,SUZUKI Tomomichi¹

Affiliation:

1. Department of Industrial Administration, Faculty of Science and Technology, Tokyo University of Science

2. Department of Economic Information, Faculty of Economic Information, Onomichi City University

3. Department of Mathematical Analysis and Statistical Inference, The Institute of Statistical Mathematics

Publisher

The Japanese Society for Quality Control

Link

https://www.jstage.jst.go.jp/article/tqs/3/2/3_46/_pdf

Reference10 articles.

1. 1 Ajay Kumar (2002), “Neural network based detection of local textile defects”, Pattern Recognition, 36(7):1645-1659.

2. 2 Bahman Jamshidi Eini, Abbas Saghaei, S. Hossein Hosseini, Ali Hamedanian (2013), “Defect detection and preventive maintenance prioritization of distribution cubicles by infrared statistical image processing”, Proceedings of 22nd International Conference and Exhibition on Electricity Districution.

3. 3 G. M. Rahaman, Md. Mobarak Hossain (2009), “Automatic defect detection and classification technique from image: a special case using ceramic tiles”, International Journal of Computer Science and Information and Security, 1(1):22-33.

4. 4 Leo Breiman (2001), “Random Forests”, Machine Learning, Vol.45, No.1, pp. 5-32.

5. 5 Natsuki Sano, Yuki Mori, Tomomichi Suzuki (2016), “Defect Detection using two-dimensional moving range filter and unanimous vote among color component classifiers” Proceedings of the 3rd multidisciplinary International Social Networks Conference.

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