AUTOMATIC BUILDING DAMAGE DETECTION METHOD USING HIGH-RESOLUTION REMOTE SENSING IMAGES AND 3D GIS MODEL

8 citations as recorded by crossref.

1. A Model Study of Building Seismic Damage Information Extraction and Analysis on Ground‐Based LiDAR Data F. Yang et al.
2. Remote Sensing-Based Proxies for Urban Disaster Risk Management and Resilience: A Review S. Ghaffarian et al.
3. SCE-Net: Self- and Cross-Enhancement Network for Single-View Height Estimation and Semantic Segmentation S. Xing et al.
4. Disaster damage detection through synergistic use of deep learning and 3D point cloud features derived from very high resolution oblique aerial images, and multiple-kernel-learning A. Vetrivel et al.
5. Spatial Resolution as a Factor for Efficient UAV-Based Weed Mapping—A Soybean Field Case Study N. Ubben et al.
6. Generating 3D city models without elevation data F. Biljecki et al.
7. Hurricane damage assessment using coupled convolutional neural networks: a case study of hurricane Michael P. Berezina & D. Liu
8. Bilevel Thresholding–Based Iterative Analysis for Building-Surface Damage Detection in a Postearthquake Environment M. Areti & Z. Hasnain