A Swin Transformer + U-Net hybrid with a watershed loss achieves slightly higher PSNR/SSIM than prior dehazing methods on the RICE and SateHaze1k benchmarks.
A survey on deep learning-based change detection from high-resolution remote sensing images
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
REJECT 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Satellite Image Utilization for Dehazing with Swin Transformer-Hybrid U-Net and Watershed loss
A Swin Transformer + U-Net hybrid with a watershed loss achieves slightly higher PSNR/SSIM than prior dehazing methods on the RICE and SateHaze1k benchmarks.