SD-IDD: Selective Distillation for Incremental Defect Detection
Surface defects in industrial production are complex and diverse. Therefore, deep learning-based defect detection models must consistently adapt to newly emerging defect categories. The trained models generally suffer from catastrophic forgetting as they learn new defect categories. To address this...
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| Autores principales: | , , , |
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| Formato: | Artigo |
| Lenguaje: | Inglês |
| Publicado: |
MDPI AG
2026-02-01
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| Colección: | Sensors |
| Materias: | |
| Acceso en línea: | https://www.mdpi.com/1424-8220/26/5/1413 |
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