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Towards Efficient Disaster Response via Cost-effective Unbiased Class Rate Estimation through Neyman Allocation Stratified Sampling Active Learning
With the rapid development of earth observation technology, we have entered an era of massively available satellite remote-sensing data.
Flood Data Analysis on SpaceNet 8 Using Apache Sedona
This platform aims to enhance the efficiency of error analysis, a critical aspect of improving flood damage detection accuracy.
Learning from Multimodal and Multitemporal Earth Observation Data for Building Damage Mapping
In this study, we have developed a global multisensor and multitemporal dataset for building damage mapping.
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