See, Perceive, and Answer: A Unified Benchmark for High-Resolution Postdisaster Evaluation in Remote Sensing Images
Author:
Affiliation:
1. Image Processing Center, School of Astronautics, Beihang University, Beijing, China
Funder
National Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/36/10354519/10496308.pdf?arnumber=10496308
Reference72 articles.
1. Airport Detection Based on a Multiscale Fusion Feature for Optical Remote Sensing Images
2. Geospatial Object Detection In Remote Sensing Images Based On Multi-Scale Convolutional Neural Networks
3. Object detection in optical remote sensing images: A survey and a new benchmark
4. Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery
5. Do Game Data Generalize Well for Remote Sensing Image Segmentation?
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1. Disaster Management Redefined: Integrating SVM-AE Techniques with Remote Sensing and Meteorological Data;Remote Sensing in Earth Systems Sciences;2024-09-02
2. Panoptic Perception: A Novel Task and Fine-Grained Dataset for Universal Remote Sensing Image Interpretation;IEEE Transactions on Geoscience and Remote Sensing;2024
3. A Comparative Analysis of Post-Disaster Analysis Using Image Processing Techniques;E3S Web of Conferences;2024
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