A Hierarchical Machine Learning Approach for Multi-Level and Multi-Resolution 3D Point Cloud Classification

The recent years saw an extensive use of 3D point cloud data for heritage documentation, valorisation and visualisation. Although rich in metric quality, these 3D data lack structured information such as semantics and hierarchy between parts. In this context, the introduction of point cloud classifi...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Simone Teruggi, Eleonora Grilli, Michele Russo, Francesco Fassi, Fabio Remondino
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2020-08-01
Sarja:	Remote Sensing
Aiheet:	machine learning 3D architectural heritage multi-resolution point cloud classification Random Forest
Linkit:	https://www.mdpi.com/2072-4292/12/16/2598
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!