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Local region-learning modules for point cloud classification
At each level, the point cloud is sampled to extract representative points and these points are used to be centers of local regions.
Using t-distributed stochastic neighbor embedding for visualization and segmentation of 3D point clouds of plants
In this work, the use of t-SNE is proposed to embed 3D point clouds of plants into 2D space for plant characterization.
Assigning Apples to Individual Trees in Dense Orchards using 3D Color Point Clouds
We propose a 3D color point cloud processing pipeline to count apples on individual apple trees in trellis structured orchards.
Segmentation of structural parts of rosebush plants with 3D point-based deep learning methods
We adapted six recent point-based deep learning architectures (PointNet, PointNet++, DGCNN, PointCNN, ShellNet, RIConv) for segmentation of structural parts of rosebush models.
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