CryoNet, a ResNet101-based encoder-decoder CNN with scSE attention, reports 90.52% overall IoU and 90.46% IoU on debris-covered glaciers in the Poiqu Basin using multi-modal Sentinel-2 and auxiliary data, outperforming DeepLabV3+, SegFormer, and U-Net while transferring to the Mont Blanc Massif.
Recalibrating Fully Convo- lutional Networks With Spatial and Channel ’Squeeze and Excitation’ Blocks
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CryoNet: A Deep Learning Framework for Multi-Modal Debris-Covered Glacier Mapping. A Case Study of the Poiqu Basin, Central Himalaya
CryoNet, a ResNet101-based encoder-decoder CNN with scSE attention, reports 90.52% overall IoU and 90.46% IoU on debris-covered glaciers in the Poiqu Basin using multi-modal Sentinel-2 and auxiliary data, outperforming DeepLabV3+, SegFormer, and U-Net while transferring to the Mont Blanc Massif.