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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.

, , , , , и . IGARSS, стр. 3579-3582. IEEE, (2015)

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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., , , , , и . IGARSS, стр. 3579-3582. IEEE, (2015)Technical Solution Discussion for Key Challenges of Operational Convolutional Neural Network-Based Building-Damage Assessment from Satellite Imagery: Perspective from Benchmark xBD Dataset., , , , , , , и . Remote. Sens., 12 (22): 3808 (2020)Optimizing the Post-disaster Resource Allocation with Q-Learning: Demonstration of 2021 China Flood., , , и . DEXA (2), том 13427 из Lecture Notes in Computer Science, стр. 256-262. Springer, (2022)Flood Inundation Depth Estimation from SAR-Based Flood Extent and DEM., , и . IGARSS, стр. 337-340. IEEE, (2023)Exploring the Feasibility of Ray Tracing SAR Simulation on Building Damage Assessment., , , и . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2024)Towards Efficient Disaster Response via Cost-effective Unbiased Class Rate Estimation through Neyman Allocation Stratified Sampling Active Learning., , , , , и . CoRR, (2024)Extraction of damaged areas due to the 2013 Haiyan Typhoon using ASTER data., , , , , и . IGARSS, стр. 2154-2157. IEEE, (2014)Damage detection due to the typhoon haiyan from high-resolution SAR images., , , , и . IGARSS, стр. 4828-4831. IEEE, (2014)A Case-Based Reasoning Framework Augmented with Causal Graph Bayesian Networks for Multi-Hazard Assessment of Earthquake Impacts., , , , , , , и . ICCBR Workshops, том 3708 из CEUR Workshop Proceedings, стр. 206-219. CEUR-WS.org, (2024)Pyramid Pooling Module-Based Semi-Siamese Network: A Benchmark Model for Assessing Building Damage from xBD Satellite Imagery Datasets., , , , , , , , и . Remote. Sens., 12 (24): 4055 (2020)