ESDSCNet: an enhanced shallow feature difference and semantic context network for remote sensing change detection: with building change detection as a case
Author:
Affiliation:
1. School of Information Engineering, China University of Geosciences (Beijing), Beijing, China
2. Natural Resources Survey and Monitoring Research Centre, Chinese Academy of Surveying & Mapping, Beijing, China
Funder
the State Key Laboratory of Geo-Information Engineering and Key Laboratory of Surveying and Mapping Science and Geospatial Information Technology of MNR, CASM
the Fundamental Research Funds for the Central Universities
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences
Link
https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2225712
Reference55 articles.
1. Multi-scale hierarchical sampling change detection using Random Forest for high-resolution satellite imagery
2. Automatic analysis of the difference image for unsupervised change detection
3. Unsupervised Change Detection in Satellite Images Using Principal Component Analysis and $k$-Means Clustering
4. A hierarchical self-attention augmented Laplacian pyramid expanding network for change detection in high-resolution remote sensing images
5. A Spatial-Temporal Attention-Based Method and a New Dataset for Remote Sensing Image Change Detection
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