A deep learning approach to defect detection with limited data availability
In industrial processes, products are often visually inspected for defects inorder to verify their quality. Many automated visual inspection algorithms exist, and in many cases humans still perform the inspections. Advances in machine learning have showed that deep learning methods lie at the forefr...
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| Format: | Others |
| Language: | English |
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Umeå universitet, Institutionen för fysik
2020
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-173207 |