Lidar Toolbox Model for RandLA-Net Semantic Segmentation

Segment point clouds using RandLA-Net semantic segmentation network
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Mise à jour 11 sept. 2024
RandLA-Net is a widely used, fast, and efficient deep learning network designed for semantic segmentation of large-scale point clouds. RandLA-Net uses random sampling to downsample large point clouds and boost speed, while also employing a local feature aggregation module to preserve significant features, making it an efficient semantic segmentation network.
Opening the downloaded install file from your operating system or from within MATLAB will initiate the installation process for the release you have.
This network model is functional for R2024a and beyond.
Compatibilité avec les versions de MATLAB
Créé avec R2024a
Compatible avec les versions R2024a à R2024b
Plateformes compatibles
Windows macOS (Apple Silicon) macOS (Intel) Linux

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