Building Change Detection in Aerial Imagery Using End-to-End Deep Learning Semantic Segmentation Techniques
Automatic building change detection is essential for updating geospatial data, urban planning, and land use management. The objective of this study is to propose a transformer-based UNet-like framework for end-to-end building change detection, integrating multi-temporal and multi-source data to impr...
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| Main Authors: | Tee-Ann Teo, Pei-Cheng Chen |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
|
| Series: | Buildings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-5309/15/5/695 |
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