Lightweight Transformer with Adaptive Rotational Convolutions for Aerial Object Detection
Oriented object detection in aerial imagery presents unique challenges due to the arbitrary orientations, diverse scales, and limited availability of labeled data. In response to these issues, we propose RASST—a lightweight Rotationally Aware Semi-Supervised Transformer framework designed to achieve...
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| Hauptverfasser: | , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
MDPI AG
2025-05-01
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| Schriftenreihe: | Applied Sciences |
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| Online-Zugang: | https://www.mdpi.com/2076-3417/15/9/5212 |
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