The SpaceNet 8 Challenge - From Foundation Mapping to Flood Detection
Author:
Affiliation:
1. German Aerospace Center (DLR), Microwaves and Radar Institute, SAR Technology
2. Oak Ridge National Laboratory
3. Maxar Technologies
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9883023/9883024/09883741.pdf?arnumber=9883741
Reference15 articles.
1. Curating flood extent data and leveraging citizen science for benchmarking machine learning solutions;gahlot;Earth Space Sci Open Arch,2022
2. FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding
3. Deep Residual Learning for Image Recognition
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1. Introducing SpaceNet 9 - Cross-Modal Satellite Imagery Registration for Natural Disaster Responses;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07
2. SpaceNet 8: Winning Approaches to Multi-Class Feature Segmentation from Satellite Imagery for Flood Disasters;IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium;2023-07-16
3. UMiT-Net: A U-Shaped Mix-Transformer Network for Extracting Precise Roads Using Remote Sensing Images;IEEE Transactions on Geoscience and Remote Sensing;2023
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