Light SDI-NAS: Lightweight Convolutional Neural Networks for Surface Defect Segmentation Based on Neural Architecture Search
Convolutional neural networks (CNNs) have achieved remarkable performance in industrial image-based surface defect inspection in recent years. However, many state-of-the-art (SOTA) networks have become increasingly complex and computationally expensive, which limits their deployment in resource-cons...
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| Main Authors: | , , , |
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| Format: | Artigo |
| Language: | Inglês |
| Published: |
MDPI AG
2026-04-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/16/8/3875 |
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