The ALS point clouds allow an automated analysis of large areas in terms of assigning a (semantic) class label to each point of the considered 3D point cloud.
(PDF) A Convolutional Neural Network-Based 3D Semantic ...
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Jun 9, 2024 · 3D semantic labeling is a fundamental task in airborne laser scanning (ALS) point clouds processing. The complexity of observed scenes and ...
A point-based feature image-generation method is proposed that transforms the 3D neighborhood features of a point into a 2D image and achieves 82.3% overall ...
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Abstract: 3D semantic labeling is a fundamental task in airborne laser scanning (ALS) point clouds processing. The complexity of observed scenes and the ...
Recently the ISPRS WG II/4 provides a benchmark on 3D semantic labelling, a convolutional neural network based method achieves the best overall accuracy ...
Dec 29, 2020 · In this paper, we introduce an efficient discretization based framework according to the geometric character of ALS point clouds.
This work presents a neural network based on PointNet that directly uses 3D point clouds, along with any attributes attached to the points, as input, and ...
Recently the ISPRS WG II/4 provides a benchmark on 3D semantic labelling, a convolutional neural network based method achieves the best overall accuracy ...
In this study, we propose a deep-learning-based weakly supervised framework for the semantic segmentation of ALS point clouds.
Oct 7, 2018 · A convolutional neural network-based 3d semantic labeling method for als point clouds. Remote Sens. 2017;9:936. doi: 10.3390/rs9090936. [DOI] ...