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DSTEELNet: A Real-Time Parallel Dilated CNN with Atrous Spatial Pyramid Pooling for Detecting and Classifying Defects in Surface Steel Strips
Automatic defects inspection and classification demonstrate significant importance in improving quality in the steel industry. This paper proposed and developed DSTEELNet convolution neural network (CNN) architecture to improve detection accuracy and the required time to detect defects in surface st...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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MDPI
2023
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9824085/ https://www.ncbi.nlm.nih.gov/pubmed/36617141 http://dx.doi.org/10.3390/s23010544 |