Concatenated Network Fusion Algorithm (CNFA) Based on Deep Learning: Improving the Detection Accuracy of Surface Defects for Ceramic Tile
The low accuracy of detection algorithms is one impediment in detecting ceramic tile’s surface defects online utilizing intelligent detection instead of human inspection. The purpose of this paper is to present a CNFA for resolving the obstacle. Firstly, a negative sample set is generated online by...
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| Autori principali: | , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
MDPI AG
2022-01-01
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| Serie: | Applied Sciences |
| Soggetti: | |
| Accesso online: | https://www.mdpi.com/2076-3417/12/3/1249 |
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