CLOI-NET: Class segmentation of industrial facilities’ point cloud datasets

Author:

Agapaki Eva,Brilakis Ioannis

Funder

EPSRC

US National Academy of Engineering

AVEVA Group Plc.

BP International Centre for Business and Technology

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems

Reference155 articles.

1. E. Agapaki, I. Brilakis, Prioritising object types of industrial facilities to reduce as-is modelling time, in: Proceeding of the 33rd Annual ARCOM Conference, 4–6 September 2017, Cambridge, U.K., 2017, pp. 402–411.

2. CLOI: A shape classification benchmark dataset for industrial facilities;Agapaki,2019

3. Prioritizing object types for modelling existing industrial facilities;Agapaki;Autom. Construct.,2018

4. Anuraag Agrawal, Atsushi Nakazawa, Haruo Takemura, MMM-classification of 3D range data, in: Proceedings – IEEE International Conference on Robotics and Automation, 2009. ISBN 9781424427895. doi: 10.1109/ROBOT.2009.5152539.

5. Automatic detection of cylindrical objects in built facilities;Ahmed;J. Comput. Civil Eng.,2014

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