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.
Error sources and guidelines for quality assessment of glacier area, elevation change, and velocity products derived from satellite data in the Glaciers cci project,
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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.