Comparing Machine and Deep Learning Methods for Large 3D Heritage Semantic Segmentation. - Francesca Matrone; Eleonora Grilli; Massimo Martini; Marina Paolanti; Roberto Pierdicca; Fabio Remondino (ISPRS Int. J. Geo Inf., 2020)

Point Cloud Semantic Segmentation Using a Deep Learning Framework for Cultural Heritage. - Roberto Pierdicca; Marina Paolanti; Francesca Matrone; Massimo Martini; Christian Morbidoni; Eva Savina Malinverni; Emanuele Frontoni; Andrea Maria Lingua (Remote. Sens., 2020)

A BIM-GIS Integrated Database to Support Planned Maintenance Activities of Historical Built Heritage. - Elisabetta Colucci; Emmanuele Iacono; Francesca Matrone; Gianvito Marino Ventura (ASITA, 2021)

Detection of Wet Riparian Areas using Very High Resolution Multispectral UAS Imagery Based on a Feature-based Machine Learning Algorithm. - Masoume Mahboubi; Elena Belcore; Emanuele Pontoglio; Francesca Matrone; Andrea Lingua (AGILE Conf., 2022)

BubblEX: An Explainable Deep Learning Framework for Point-Cloud Classification. - Francesca Matrone; Marina Paolanti; Andrea Felicetti; Massimo Martini; Roberto Pierdicca (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022)

Artificial Intelligence for the analysis of Cultural Heritage point clouds. - Marina Paolanti; Francesca Matrone; Tiberio Uricchio; Benedetta Giovanola; Emanuele Frontoni; Andrea Maria Lingua; Roberto Pierdicca (DH, 2023)

The HBIM-GIS Main10ance Platform to Enhance the Maintenance and Conservation of Historical Built Heritage. - Francesca Matrone; Elisabetta Colucci; Emmanuele Iacono; Gianvito Marino Ventura (Sensors, 2023)

Enhancing explainability of deep learning models for point cloud analysis: a focus on semantic segmentation. - Francesca Matrone; Marina Paolanti; Emanuele Frontoni; Roberto Pierdicca (Int. J. Digit. Earth, 2024)