Hierarchical Probabilistic Graphical Models and Deep Convolutional Neural Networks for Remote Sensing Image Classification. - Martina Pastorino; Gabriele Moser; Sebastiano B. Serpico; Josiane Zerubia (EUSIPCO, 2021)

Semantic Segmentation of Remote Sensing Images Combining Hierarchical Probabilistic Graphical Models and Deep Convolutional Neural Networks. - Martina Pastorino; Gabriele Moser; Sebastiano B. Serpico; Josiane Zerubia (IGARSS, 2021)

Multisensor and Multiresolution Remote Sensing Image Classification through a Causal Hierarchical Markov Framework and Decision Tree Ensembles. - Martina Pastorino; Alessandro Montaldo; Luca Fronda; Ihsen Hedhli; Gabriele Moser; Sebastiano B. Serpico; Josiane Zerubia (Remote. Sens., 2021)

Fully Convolutional and Feedforward Networks for The Semantic Segmentation of Remotely Sensed Images. - Martina Pastorino; Gabriele Moser; Sebastiano B. Serpico; Josiane Zerubia (ICIP, 2022)

Semantic Segmentation of SAR Images Through Fully Convolutional Networks and Hierarchical Probabilistic Graphical Models. - Martina Pastorino; Gabriele Moser; Sebastiano B. Serpico; Josiane Zerubia (IGARSS, 2022)

Multimodal Fusion of Mobility Demand Data and Remote Sensing Imagery for Urban Land-Use and Land-Cover Mapping. - Martina Pastorino; Federico Gallo; Angela Di Febbraro; Gabriele Moser; Nicola Sacco; Sebastiano B. Serpico (Remote. Sens., 2022)

Semantic Segmentation of Remote-Sensing Images Through Fully Convolutional Neural Networks and Hierarchical Probabilistic Graphical Models. - Martina Pastorino; Gabriele Moser; Sebastiano B. Serpico; Josiane Zerubia (IEEE Trans. Geosci. Remote. Sens., 2022)

Classification of Multimission SAR Images Based on Probabilistic Graphical Models and Convolutional Neural Networks. - Martina Pastorino; Gabriele Moser; Sebastiano B. Serpico; Josiane Zerubia (IGARSS, 2023)

Learning CRF potentials through fully convolutional networks for satellite image semantic segmentation. - Martina Pastorino; Gabriele Moser; Sebastiano B. Serpico; Josiane Zerubia (SITIS, 2023)

Probabilistic graphical models and deep learning methods for remote sensing image analysis. - Martina Pastorino (2023)

Probabilistic Fusion Framework Combining CNNs and Graphical Models for Multiresolution Satellite and UAV Image Classification. - Martina Pastorino; Gabriele Moser; Fabien Guerra; Sebastiano B. Serpico; Josiane Zerubia (ICPR (2), 2024)

A Multiresolution Fusion Framework based on Probabilistic Graphical Modeling for Burnt Zones Mapping from Satellite and UAV Imagery. - Martina Pastorino; Gabriele Moser; Fabien Guerra; Sebastiano B. Serpico; Josiane Zerubia (IGARSS, 2024)

Multimission, Multifrequency, and Multiresolution SAR Image Classification Through Hierarchical Markov Models and Convolutional Networks. - Martina Pastorino; Gabriele Moser; Sebastiano B. Serpico; Josiane Zerubia (IEEE Geosci. Remote. Sens. Lett., 2024)

CRFNet: A Deep Convolutional Network to Learn the Potentials of a CRF for the Semantic Segmentation of Remote Sensing Images. - Martina Pastorino; Gabriele Moser; Sebastiano B. Serpico; Josiane Zerubia (IEEE Trans. Geosci. Remote. Sens., 2024)

Deep Diffusion Models and Unsupervised Hyperspectral Unmixing for Realistic Abundance Map Synthesis. - Martina Pastorino; Michael Alibani; Nicola Acito; Gabriele Moser (CVPR Workshops, 2025)

Multiresolution Fusion and Classification of Hyperspectral and Panchromatic Remote Sensing Images. - Martina Pastorino; Gabriele Moser; Sebastiano B. Serpico; Josiane Zerubia (WACV (Workshops), 2025)

Investigating the Potential of Deep Learning Approaches in the Reconstruction of VNIR-SWIR Hyperspectral Data From Multispectral Imagery. - Michael Alibani; Martina Pastorino; Gabriele Moser; Nicola Acito (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2025)