Transformer-based models deliver strong landslide segmentation on satellite images, and parameter-efficient fine-tuning matches full fine-tuning accuracy while cutting trainable parameters by up to 95%.
Variation in the frequency and char- acteristics of landslides in response to changes in forest cover and rainfall in japan over the last century: A literature review
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A Benchmark Study of Segmentation Models and Adaptation Strategies for Landslide Detection from Satellite Imagery
Transformer-based models deliver strong landslide segmentation on satellite images, and parameter-efficient fine-tuning matches full fine-tuning accuracy while cutting trainable parameters by up to 95%.