A Significant Feature Selection to Improve the Accuracy of a Classification Algorithm for Steel Defect-Reference-Cited by-同舟云学术

A Significant Feature Selection to Improve the Accuracy of a Classification Algorithm for Steel Defect

Published:2022-09-21 Issue: Volume: Page:
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Container-title:2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA)
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Author:

Rao K. B. V. Brahma¹,Prasad G. N. R.²,Amudha S.³,Kumar Ashok⁴,Prasad DVSSSV⁵,Mohanavel V.⁶

Affiliation:

1. Koneru Lakshmaiah Education Foundation,Department of Computer Science & Engineering,Vaddeswaram,Andhra Pradesh,India

2. Chaitanya Bharathi Institute of Technology (Autonomous),Department of MCA,Gandipet,Telangana,India

3. SRM Institute of Science and Technology,Department of Computational Intelligence,Kattankulathur,Tamil Nadu,India

4. Banasthali Vidyapith,Department of Computer Science,Rajasthan,India

5. Aditya College of Engineering,Department of Mechanical Engineering,Surampalem,Andhra Pradesh,India

6. Centre for Materials Engineering and Regenerative Medicine, Bharath Institute of Higher Education and Research,Tamilnadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9985450/9985015/09985717.pdf?arnumber=9985717

Reference18 articles.

1. An evolutionary classifier for steel surface defects with small sample set

2. Research on Defect Detection Method for Steel Metal Surface based on Deep Learning

3. A PRISMA-driven systematic review of data mining methods used for defects detection and classification in the manufacturing industry

4. Steel Surface Defects Detection and Classification Using SIFT and Voting Strategy;suvdaa;International Journal of Software Engineering and Its Applications,2012

5. Steel Defect Classification Using Machine Learning

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