BNResNet: Batch Normalization-Inspired Deep Bottleneck Residual Architecture for Aerial Scene Recognition in Low-Contrast Remote Sensing Images
Remote sensing (RS) images are evolving daily for their applications in surveillance, planned urbanization, law enforcement, climate change detection, agriculture, and monitoring catastrophes. Artificial intelligence techniques in this application heavily depend on the quality of RS images. The low-...
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| Автори: | , , , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
IEEE
2025-01-01
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| Серія: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Предмети: | |
| Онлайн доступ: | https://ieeexplore.ieee.org/document/11108310/ |
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