Lidar Toolbox Model for RandLA-Net Semantic Segmentation

Segment point clouds using RandLA-Net semantic segmentation network
40 Downloads
Updated 11 Sep 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.
MATLAB Release Compatibility
Created with R2024a
Compatible with R2024a to R2024b
Platform Compatibility
Windows macOS (Apple silicon) macOS (Intel) Linux

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