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Damage detection due to the typhoon haiyan from high-resolution SAR images.

, , , , and . IGARSS, page 4828-4831. IEEE, (2014)

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Towards Efficient Disaster Response via Cost-effective Unbiased Class Rate Estimation through Neyman Allocation Stratified Sampling Active Learning., , , , , and . CoRR, (2024)Developing a method for urban damage mapping using radar signatures of building footprint in SAR imagery: A case study after the 2013 Super Typhoon Haiyan., , , , , and . IGARSS, page 3579-3582. IEEE, (2015)Optimizing the Post-disaster Resource Allocation with Q-Learning: Demonstration of 2021 China Flood., , , and . DEXA (2), volume 13427 of Lecture Notes in Computer Science, page 256-262. Springer, (2022)Technical Solution Discussion for Key Challenges of Operational Convolutional Neural Network-Based Building-Damage Assessment from Satellite Imagery: Perspective from Benchmark xBD Dataset., , , , , , , and . Remote. Sens., 12 (22): 3808 (2020)Exploring the Feasibility of Ray Tracing SAR Simulation on Building Damage Assessment., , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2024)Building Damage Mapping of the 2024 Noto Peninsula Earthquake, Japan, Using Semi-Supervised Learning and VHR Optical Imagery., , , , , and . IEEE Geosci. Remote. Sens. Lett., (2024)Flood Inundation Depth Estimation from SAR-Based Flood Extent and DEM., , and . IGARSS, page 337-340. IEEE, (2023)Extraction of damaged areas due to the 2013 Haiyan Typhoon using ASTER data., , , , , and . IGARSS, page 2154-2157. IEEE, (2014)Damage detection due to the typhoon haiyan from high-resolution SAR images., , , , and . IGARSS, page 4828-4831. IEEE, (2014)A Case-Based Reasoning Framework Augmented with Causal Graph Bayesian Networks for Multi-Hazard Assessment of Earthquake Impacts., , , , , , , and . ICCBR Workshops, volume 3708 of CEUR Workshop Proceedings, page 206-219. CEUR-WS.org, (2024)