Automated paper impurities evaluation using feature representations based on ADMM sparse codes-Reference-Cited by-同舟云学术

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Automated paper impurities evaluation using feature representations based on ADMM sparse codes

Published:2018-02-27 Issue:2 Volume:34 Page:797-805
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Huangpeng Qizi¹,Huang Wenwei²,Shi Hanyi³

Affiliation:

1. College of Information System and Management, National University of Defense Technology, Changsha, P.R. China

2. College of Nine, National University of Defense Technology, Changsha, P.R. China

3. College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, P.R. China

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference25 articles.

1. A sequential machine vision procedure for assessing paper impurities;Bianconi;Computers in Industry,2014

2. Feng T. , Zou L. , Yan J. , Shi W. , Liu Y. , Fan C. and Deng D. , Real-time fabric defect detection using accelerated small-scale over-completed dictionary of sparse coding, International Journal of Advanced Robotic Systems (2016).

3. Evaluation of the effects of Gabor filter parameters on texture classification;Bianconia;Pattern Recognition,2007

4. Weimera D. , Thamer H. and Scholz-Reiter B. , Learning defect classifiers for textured surfaces using neural networks and statistical feature representations, In CIRP 7 (2013).

5. Automated surface inspection of cold-formed micro-parts;Scholz-Reiter;CIRP Annals - Manufacturing Technology,2012

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