Automatic detection and classification of manufacturing defects in metal boxes using deep neural networks.
This paper develops a new machine vision framework for efficient detection and classification of manufacturing defects in metal boxes. Previous techniques, which are based on either visual inspection or on hand-crafted features, are both inaccurate and time consuming. In this paper, we show that by...
Main Authors: | Oumayma Essid, Hamid Laga, Chafik Samir |
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Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2018-01-01
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Series: | PLoS ONE |
Online Access: | http://europepmc.org/articles/PMC6226149?pdf=render |
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