Setting up model training for classification and segmentation of point clouds

The features and capabilities of the PointNet neural network architecture in relation to artificially generated clouds of laser reflection points in the Terra$\underline{\ }$Maker information system are presented. The results of training by the Paintnet network are analyzed and the accuracy of the obtained models and graphs is evaluated. An approach is proposed to determine the parameters that give maximum accuracy when performing experiments on the example of point clouds obtained from the Terra$\underline{\ }$Maker information system.