Machine Learning Applied to LiDAR Data for Cultural Heritage
December 6th, 2023, h 9.30-17.30 CET
online via Microsoft Teams:
This workshop will delve into the combined expertise in the fields of Machine Learning, Remote Sensing and Landscape Archaeology. This initiative is a significant component of the ‘OPtimal Transport for Identifying Marauder Activities on LiDAR’ (OPTIMAL) project, which has received funding from the European Union's Horizon 2020 Research and Innovation programme under grant agreement Nº10102795.
Agenda
Welcome address
Arianna Traviglia - Centre for Cultural Heritage Technology - Istituto Italiano di Tecnologia
9:00-9:40
The OPTIMAL projects
Marco Fiorucci - Centre for Cultural Heritage Technology - Istituto Italiano di Tecnologia
9:40-9:50
Optimal transport and machine Learning (keynote talk)
Makoto Yamada - Okinawa Institute of Technology (OIST)
9:50-10:50
COFFEE BREAK
10:50-11:00
Applying machine learning for archaeological prospection in remotely sensed data: Challenges and opportunities
Wouter Verschoof-van der Vaart - Nederlands Forensisch Instituut
11:00-11:30
Airborne LIDAR for the detection of archaeological features (keynote talk)
Žiga Kokalj - Research Centre of the Slovenian Academy of Sciences and Arts
11:30-12:30
LUNCH BREAK
12:30-14:00
Machine learning and LiDAR visualizations techniques for archaeology
Raveerat Jaturapitpornchai -Centre for Cultural Heritage Technology - Istituto Italiano di Tecnologia
14:00-14:30
Looting: a pressing problem on a global scale
Riccardo Giovanelli - Centre for Cultural Heritage Technology - Istituto Italiano di Tecnologia
14:30-15:00
COFFEE BREAK
15:00-15:15
Optimal transport for looting detection on LIDAR point clouds
Marco Fiorucci - Centre for Cultural Heritage Technology - Istituto Italiano di Tecnologia
15:15-15:45
Deep Learning for looting detection on multispectral data (ALCEO)
Gregory Sech - Centre for Cultural Heritage Technology - Istituto Italiano di Tecnologia
15:45-16:15
Implicit learning for looting detection on LIDAR point clouds
Peter Naylor - ESA ESRIN-Φ-lab
16:15-16:45
CLOSED REMARKS
16:45-17:00