首页|Studies from Silesian University of Technology Reveal New Findings on Machine Learning (Visual Programming Simulator for Producing Realistic Labeled Point Clouds From Digital Infrastructure Models)
Studies from Silesian University of Technology Reveal New Findings on Machine Learning (Visual Programming Simulator for Producing Realistic Labeled Point Clouds From Digital Infrastructure Models)
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NETL
NSTL
Elsevier
Current study results on Machine Learning have been published. According to news reporting originating from Gliwice, Poland, by NewsRx correspondents, research stated, “The increasing availability of point clouds has led to intensive research into automating point cloud processing using machine learning. While supervised systems require large and diverse labeled datasets, the cost and time of manual data creation can be overcome with synthetic data.” Funders for this research include European Social Fund (ESF), Silesian University of Technology Excellence Initiative grant. Our news editors obtained a quote from the research from the Silesian University of Technology, “This paper introduces DynamoPCSim, a versatile scanning simulator based on visual programming, implementing ray tracing, and operating on BIM models. The simulator collects measurements of digital models and transfers the model semantic data to generated point clouds, enabling automated labeling. Customizable scanning parameters allow for the reflection of real scanners (including imperfections) and the transformation of synthetic point clouds, making the data more realistic.”
GliwicePolandEuropeCyborgsEmerging TechnologiesMachine LearningSilesian University of Technology
NETL
NSTL
Elsevier
