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Abstract <p>The features and capabilities of the PointNet neural network architecture in relation to artificially generated clouds of laser reflection points in the Terra_Maker information system are presented. The results of training by the PointNet network are analyzed, and the accuracy of the obtained models and graphs is evaluated. An approach is proposed to determine the parameters providing maximum accuracy when performing experiments on the example of point clouds obtained from the Terra_Maker information system.</p>

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On the Issue of Setting Up Model Training in the Classification and Segmentation of Point Clouds

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • D. A. Gura,
  • R. A. Dyachenko,
  • E. S. Boyko,
  • D. A. Levchenko

摘要

Abstract

The features and capabilities of the PointNet neural network architecture in relation to artificially generated clouds of laser reflection points in the Terra_Maker information system are presented. The results of training by the PointNet network are analyzed, and the accuracy of the obtained models and graphs is evaluated. An approach is proposed to determine the parameters providing maximum accuracy when performing experiments on the example of point clouds obtained from the Terra_Maker information system.