An Automated Visual Defect Segmentation for Flat Steel Surface Using Deep Neural Networks-Reference-Cited by-同舟云学术

An Automated Visual Defect Segmentation for Flat Steel Surface Using Deep Neural Networks

Published:2022-11-17 Issue: Volume: Page:
ISSN:
Container-title:2022 12th International Conference on Computer and Knowledge Engineering (ICCKE)
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Author:

Sabet D. Nourbakhsh¹,Zarifi M. R.¹,Khoramdel J.²,Borhani Y.¹,Najafi E.¹

Affiliation:

1. K. N. Toosi University of Technology,Center of Excellence in Robotics and Control, Advanced Robotics & Automated Systems (ARAS) Faculty of Mechanical Engineering,Tehran,Iran

2. Tarbiat Modares University,Faculty of Mechanical Engineering,Tehran,Iran

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9959861/9959975/09959998.pdf?arnumber=9959998

Reference16 articles.

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2. U-net: Convolutional networks for biomedical image segmentation;ronneberger;Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention,2015

3. Automated Detection of Steel Defects via Machine Learning based on Real-Time Semantic Segmentation

4. Boosted Dense Segmentation Networks For Constrained Distributed Systems

5. TLU-Net: A Deep Learning Approach for Automatic Steel Surface Defect Detection

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