Marco Fiorucci is a Researcher in Machine Learning at the Centre for Cultural Heritage Technology (CCHT) at the Istituto Italiano di Tecnologia. His research interests encompass machine learning and computer vision, with a strong emphasis on optimal transport and implicit neural learning, particularly as these methodologies apply to remote sensing data. He was awarded an MSCA-IF for his OPTIMAL project, which aims to develop an efficient machine learning approach based on optimal transport to automatically detect looting (both past and present) from airborne LiDAR point cloud time series. He holds a PhD in Computer Science from Ca’ Foscari University of Venice (2019) and possesses a rich interdisciplinary background that spans computer science, physics, and machine learning. His academic journey includes visiting research positions at Kyoto University (Japan), the University of Alicante (Spain), and the VTT Technical Research Centre of Finland.
Phone
+39 041 2346757
Address
Campus Scientifico Ca' Foscari Edificio Epsilon Via Torino, 155 30170 - Mestre (VE)
Research center
CCHT@Ca'Foscari Venezia
About
All Publications
2024
Jaturapitpornchai R., Poggi G., Sech G., Kokalj Z., Fiorucci M., Traviglia A.
Impact of LiDAR visualisations on semantic segmentation of archaeological objects
International Geoscience and Remote Sensing Symposium (IGARSS)
2024
Naylor P., Di Carlo D., Traviglia A., Yamada M., Fiorucci M.
Implicit Neural Representation for Change Detection
2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024, pp. 935-945
2024
Sech G., Poggi G., Ljubenovic M., Fiorucci M., Traviglia A.
Pansharpening of PRISMA products for archaeological prospection
International Geoscience and Remote Sensing Symposium (IGARSS)
2023
Fiorucci M., Naylor P., Yamada M.
Optimal Transport for Change Detection on LiDAR Point Clouds
Digest - International Geoscience and Remote Sensing Symposium (IGARSS), pp. 982-985
2023
Sech G., Soleni P., Verschoof-van der Vaart B., Kokalj Z., Traviglia A., Fiorucci M.
Transfer Learning of Semantic Segmentation Methods for Identifying Buried Archaeological Structures On LiDAR Data
Digest - International Geoscience and Remote Sensing Symposium (IGARSS), pp. 6987-6990
Dissemination
2019
Fiorucci M.
L'intelligenza artificiale a servizio dell'arte
Databeers Venezia
Public Event
Scientific Talks
2023
Fiorucci M.
Implicit Learning for Unsupervised Change Detection
Kyoto University
Institute
2023
Fiorucci M.
OPtimal Transport for Identifying Marauder Activities on Lidar
Okinawa Institute of Technology (Okinawa, Japan)
Institute
2023
Fiorucci M.
Scalable Unbalanced Optimal Transport for Change Detection
The Institute of Statistical Mathematics, Tokyo
Institute
2023
Fiorucci M.
Unbalanced Optimal Transport for Change Detection
Osaka University
Institute
2018
Fiorucci M.
Graph Summarization Using Regular Partition and Its Use in Graph Search
Department of Mathematics and Systems Analysis, Aalto University
Institute
Oral presentations
2023
Fiorucci M., Naylor P., Yamada M.
Optimal Transport for Change Detection on LiDAR Point Clouds
Digest - International Geoscience and Remote Sensing Symposium (IGARSS), pp. 982-985
Conference
2019
Traviglia A., Fiorucci M.
Graph Convolutional Neural Networks for Cultural Heritage: Applications in RS recognition, numismatics and epigraphy
Machine Learning in Archaeology, Rome
Conference
2018
Pelosin F., Fiorucci M., and Pelillo M.
Graph Summarization Using Regular Partitions
The 8th International Conference on Network Analysis, Moscow
Conference
Editorships
2020-2021
Traviglia A., Artesani A., Fiorucci M., Ljubenovic M.
European Physical Journal Plus
Colleagues of Cultural Heritage Technologies
