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Pierluigi Arzu

Biographic Data

ID4435243
NAMEPierluigi Arzu
GIVEN NAMESPierluigi
FAMILY NAMEArzu
SIGNATUREARZU P
VERIFIEDNo
TOTAL WORKS1
TOTAL CITATIONS1
AUTHOR COUNT1
EDITOR COUNT0
FIRST PUBLICATION YEAR2025
LATEST PUBLICATION YEAR2025
H-INDEX1
  • An Open-Source Machine Learning–Based Methodological Approach for Processing High-Resolution UAS LiDAR Data in Archaeological Contexts

    Open Access•Nicodemo Abate, Dimitris Roubis et al.•ARTICLE•Journal of Archaeological Method…•2025•Cited by: 1•References: 3

    This study shows and discusses an innovative approach devised for archaeological feature detection using unmanned aerial system (UAS) LiDAR and an open-source probabilistic machine learning framework. The methodology employs a Random Forest classification algorithm within CloudCompare’s 3DMASC plugin to analyse dense LiDAR point clouds. The main steps include classifier training, hyperparameter adjustment and point cloud segmentation to produce d…

  • An Open-Source Machine Learning–Based Methodological Approach for Processing High-Resolution UAS LiDAR Data in Archaeological Contexts

    Open Access•Nicodemo Abate, Dimitris Roubis et al.•ARTICLE•Journal of Archaeological Method…•2025•Cited by: 1•References: 3

    This study shows and discusses an innovative approach devised for archaeological feature detection using unmanned aerial system (UAS) LiDAR and an open-source probabilistic machine learning framework. The methodology employs a Random Forest classification algorithm within CloudCompare’s 3DMASC plugin to analyse dense LiDAR point clouds. The main steps include classifier training, hyperparameter adjustment and point cloud segmentation to produce d…

  • An Open-Source Machine Learning–Based Methodological Approach for Processing High-Resolution UAS LiDAR Data in Archaeological Contexts

    Open Access•Nicodemo Abate, Dimitris Roubis et al.•ARTICLE•Journal of Archaeological Method…•2025•Cited by: 1•References: 3

    This study shows and discusses an innovative approach devised for archaeological feature detection using unmanned aerial system (UAS) LiDAR and an open-source probabilistic machine learning framework. The methodology employs a Random Forest classification algorithm within CloudCompare’s 3DMASC plugin to analyse dense LiDAR point clouds. The main steps include classifier training, hyperparameter adjustment and point cloud segmentation to produce d…

3D Surveying and Cultural Heritage (1 works) · Archaeological Research and Protection (1 works) · Archaeology (1 works) · Artificial Intelligence (1 works) · Computer Science (1 works) · Geography (1 works) · Geology (1 works) · High resolution (1 works) · History (1 works) · History (1 works)

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