๐ Adapting Segment Anything Model for Snow Avalanche Segmentation
Promptable foundation models represent a paradigm shift in artificial intelligence ๐. Unlike traditional task-specific networks, these large-scale pre-trained architectures are adaptable across domains using flexible prompts. Originally designed for natural imagery, models like the Segment Anything framework demonstrate zero-shot and few-shot capabilities, unlocking powerful cross-domain generalization potential. When transferred into Synthetic Aperture Radar (SAR) remote sensing, they offer a transformative approach to environmental hazard monitoring. 2️⃣ Understanding SAR Remote Sensing ๐ a) Characteristics of SAR Data Operates in all-weather, day-and-night conditions Captures backscatter intensity and texture Sensitive to surface roughness and moisture b) Challenges in SAR Interpretation Speckle noise interference Complex terrain scattering Limited annotated datasets These challenges make precise snow avalanche segmentation both critical and technically demanding. 3️⃣ The Ro...