Learning From Detailed Maps: Joint 2D-3D Semantic Segmentation for Airborne Data with Selective Label Fusion
Objects for topographic maps are often extracted manually by interpreting and segmenting airborne data, such as 2D images and 3D point clouds. Deep learning (DL) with semantic segmentation can automate this process using existing maps as ground labels. However, current map-based DL methods are limit...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2025-07-01
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| Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-annals.copernicus.org/articles/X-G-2025/101/2025/isprs-annals-X-G-2025-101-2025.pdf |
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