activity
20202022
most citedGeometric Digital Twinning of Industrial Facilities: Retrieval of Industrial Shapes

9 citations · 11 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CY20222 cited

Airport Digital Twins for Resilient Disaster Management Response

Eva Agapaki

Airports are constantly facing a variety of hazards and threats from natural disasters to cybersecurity attacks and airport stakeholders are confronted with making operational deci…

cs.CV2022

Synthetic Point Cloud Generation for Class Segmentation Applications

Maria Gonzalez Stefanelli, Avi Rajesh Jain, Sandeep Kamal Jalui +1

Maintenance of industrial facilities is a growing hazard due to the cumbersome process needed to identify infrastructure degradation. Digital Twins have the potential to improve ma…

cs.CV20229 cited

Geometric Digital Twinning of Industrial Facilities: Retrieval of Industrial Shapes

Eva Agapaki, Ioannis Brilakis

This paper devises, implements and benchmarks a novel shape retrieval method that can accurately match individual labelled point clusters (instances) of existing industrial facilit…

cs.CY2021

CLOI: An Automated Benchmark Framework For Generating Geometric Digital Twins Of Industrial Facilities

Eva Agapaki, Ioannis Brilakis

This paper devises, implements and benchmarks a novel framework, named CLOI, that can accurately generate individual labelled point clusters of the most important shapes of existin…

cs.CV2020

Instance Segmentation of Industrial Point Cloud Data

Eva Agapaki, Ioannis Brilakis

The challenge that this paper addresses is how to efficiently minimize the cost and manual labour for automatically generating object oriented geometric Digital Twins (gDTs) of ind…