DSNet enables feature fusion and detail restoration for accurate object detection in foggy conditions
Abstract In real-world scenarios, adverse weather conditions can significantly degrade the performance of deep learning-based object detection models. Specifically, fog reduces visibility, complicating feature extraction and leading to detail loss, which impairs object localization and classificatio...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-03902-y |
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