Domain adaptation of deep neural networks for tree part segmentation using synthetic forest trees

Domain adaptation of deep neural networks for tree part segmentation using synthetic forest trees

Supervised deep learning algorithms have recently achieved state-of-the-art performance in the classification, segmentation and analysis of 3D LiDAR point cloud data in a wide-range of applications and environments. One of the main downsides of deep learning-based approaches is the need for extensiv...

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Bibliographic Details
Main Authors: Mitch Bryson, Ahalya Ravendran, Celine Mercier, Tancred Frickey, Sadeepa Jayathunga, Grant Pearse, Robin J.L. Hartley
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:ISPRS Open Journal of Photogrammetry and Remote Sensing
Subjects:
Deep learning
Synthetic data
Domain adaptation
LiDAR
Laser scanning
Forests
Online Access:http://www.sciencedirect.com/science/article/pii/S266739322400022X
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