Deeply supervised network for airborne LiDAR tree classification incorporating dual attention mechanisms
Accurately identifying tree species is crucial in digital forestry. Several airborne LiDAR-based classification frameworks have been proposed to facilitate work in this area, and they have achieved impressive results. These models range from the classification of characterization parameters based on...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2024-12-01
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Series: | GIScience & Remote Sensing |
Subjects: | |
Online Access: | https://www.tandfonline.com/doi/10.1080/15481603.2024.2303866 |