Deeply supervised network for airborne LiDAR tree classification incorporating dual attention mechanisms

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...

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Bibliographic Details
Main Authors: Zhenyu Zhang, Jian Wang, Yunze Wu, Youlong Zhao, Binjie Wu
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:GIScience & Remote Sensing
Subjects:
Airborne LiDAR
point cloud
tree species classification
deep learning
attention mechanism
Online Access:https://www.tandfonline.com/doi/10.1080/15481603.2024.2303866

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