Transformer-Guided Serial Knowledge Distillation for High-Precision Anomaly Detection
Unsupervised anomaly detection (AD) remains a notable challenge in computer vision research, due to the inherent absence of annotated anomalous data and the unpredictable nature of anomaly manifestations. To address these challenges, a novel Transformer-based knowledge distillation framework is prop...
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| Główni autorzy: | , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
IEEE
2025-01-01
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| Seria: | IEEE Access |
| Hasła przedmiotowe: | |
| Dostęp online: | https://ieeexplore.ieee.org/document/11062580/ |
| Etykiety: |
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