For a complete list: google scholar
2026
[J1] M. Pastorino, G. Moser, S. B. Serpico and J. Zerubia, “Cross-Modal Fusion and Classification of Hyperspectral and Panchromatic Remote Sensing Images With Deep Learning and Multiscale CRFs,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 64, pp. 1-18, 2026, Art no. 5511318, doi: 10.1109/TGRS.2026.3686949 [link].
[J2] M. Pastorino, G. Moser, F. Guerra, S. B. Serpico and J. Zerubia, "Probabilistic Fusion Framework Based on Fully Convolutional Networks and Graphical Models for Burned Area Detection From Multiresolution Satellite and UAV Imagery," in IEEE Transactions on Geoscience and Remote Sensing, vol. 64, pp. 1-19, 2026, Art no. 4702919, doi: 10.1109/TGRS.2026.3676291 [link].
[J3] M. Pastorino, G. Moser, S. B. Serpico and J. Zerubia, "Probabilistic Graphical Models Meet Deep Learning for Semantic Segmentation: Mathematical connections and recent developments," in IEEE Signal Processing Magazine, vol. 43, no. 2, pp. 51-63, March 2026, doi: 10.1109/MSP.2025.3648958 [link].
[J4] M. Pastorino, M. Alibani, N. Acito, G. Moser, “Hyperspectral Image Synthesis Through Blind Unmixing Dictionary and Deep Diffusion Models,” IEEE Geoscience and Remote Sensing Letters, vol. 23, pp. 1-5, 2026, doi: 10.1109/LGRS.2025.3646054 [link].
2025
[J5] M. Alibani, M. Pastorino, G. Moser, N. Acito, “Investigating the Potential of Deep Learning Approaches in the Reconstruction of VNIR-SWIR Hyperspectral Data from Multispectral Imagery,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 18, pp. 14215-14227, 2025 doi: 10.1109/JSTARS.2025.3575518 [link].
[J6] M. Castiglione, F. Gallo, M. Pastorino, G. Moser, M. Nigro, N. Sacco, “Multi-source methodology for traffic analysis zones definition based on combined remote sensing and floating car data,” Journal of Transport Geography, vol. 128, 2025, doi: 10.1016/j.jtrangeo.2025.104324.
2024
[J7] M. Pastorino, G. Moser, S. B. Serpico and J. Zerubia, "CRFNet: A Deep Convolutional Network to Learn the Potentials of a CRF for the Semantic Segmentation of Remote Sensing Images," in IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-19, 2024, Art no. 4707619, doi: 10.1109/TGRS.2024.3452631 [link] [HAL link].
[J8] M. Pastorino, G. Moser, S. B. Serpico and J. Zerubia, "Multimission, Multifrequency, and Multiresolution SAR Image Classification Through Hierarchical Markov Models and Convolutional Networks," IEEE Geoscience and Remote Sensing Letters, vol. 21, pp. 1-5, 2024, Art no. 4012205, doi: 10.1109/LGRS.2024.3414284 [link] [HAL link].
2022
[J9] M. Pastorino, F. Gallo, A. Di Febbraro, G. Moser, and S. B. Serpico, “Multimodal fusion of mobility demand data and remote sensing imagery for urban land-use and land-cover mapping,” Remote Sensing, vol. 14, no. 14, 3370, Jul. 2022, doi: 10.3390/rs14143370 [link].
[J10] M. Pastorino, G. Moser, S. B. Serpico, and J. Zerubia, “Semantic Segmentation of Remote Sensing Images through Fully Convolutional Neural Networks and Hierarchical Probabilistic Graphical Models,” IEEE Transaction on Geoscience and Remote Sensing, vol. 60, pp. 1-16, 2022, Art no. 5407116, doi: 10.1109/TGRS.2022.3141996 [link] [HAL link].
2021
[J11] S. Pensieri, F. Viti, G. Moser, S. B. Serpico, L. Maggiolo, M. Pastorino, D. Solarna, A. Cambiaso, C. Carraro, C. Degano, I. Mainenti, S. Seghezza, and R. Bozzano, “Evaluating LoRaWAN Connectivity in a Marine Scenario,” Journal of Marine Science and Engineering, vol. 9, no. 11, 1218, Nov. 2021, doi: 10.3390/jmse9111218 [link].
[J12] M. Pastorino, A. Montaldo, L. Fronda, I. Hedhli, G. Moser, S. B. Serpico, and J. Zerubia, “Multisensor and Multiresolution Remote Sensing Image Classification through a Causal Hierarchical Markov Framework and Decision Tree Ensembles,” Remote Sensing, vol. 13, no. 5, p. 849, Feb. 2021, doi: 10.3390/rs13050849 [link] [HAL link].
[C1] M. Pastorino, I. Masari, G. Moser, and S. B. Serpico, "Multimodal Data Fusion for Semantic Mapping and Change Detection," in D. Lunga and R. Hänsch (eds.) GeoAI for Earth Observation Imagery: Fundamentals and Practical Applications, 1st ed. Elsevier, 2026, ch. 12, pp. 205-227, ISBN: 9780443437977.
[C2] M. Pastorino, G. Moser, S. B. Serpico, and J. Zerubia, "Convolutional Neural Networks Meet Markov Random Fields for Semantic Segmentation of Remote Sensing Images," in C. H. Chen (ed.) Signal and Image Processing for Remote Sensing, 3rd ed. Boca Raton, FL, USA: CRC Press, 2024, ch. 11, pp. 205-227, doi: 10.1201/9781003382010-14 [link].
[C3] I. Masari, M. Pastorino, G. Moser, and S. B. Serpico, "Semantic segmentation and heterogeneous change detection with SAR imagery," in F. Del Frate and M. Migliaccio (eds.) Microwave Remote Sensing of the Environment, CNIT Technical Report-15, Texmat, Rome, IT, 2024, ch. 8, ISBN: 9788894982893 [link]
2026
[P1] P. Grotti, M. Pastorino, G. Moser, “Convolutional Kolmogorov-Arnold Networks and Conditional Random Fields for Remote Sensing Image Semantic Segmentation,” IEEE International Conference on Image Processing, Tampere, (Finland), September 2026.
[P2] E. Bonadeo, M. Minetti, M. Nicora, M. Pastorino, R. Loggia, R. Golino, “Methodological Assessment and Data Preparation for LSTM-Based Residential Net-Load Forecasting,” IEEE International Conference on Environment and Electrical Engineering, Lisboa, (Portugal), July 2026.
2025
[P3] M. Pastorino, G. Moser, S. B. Serpico, J. Zerubia, “Multiresolution Fusion and Classification of Hyperspectral and Panchromatic Remote Sensing Images,” IEEE/CVF WACVW 2025 – IEEE/CVF Winter Conference on Applications of Computer Vision, Austin, TX, (USA), February – March 2025 [link][HAL link].
[P4] M. Pastorino, M. Alibani, N. Acito, G. Moser “Deep diffusion models and unsupervised hyperspectral unmixing for realistic abundance map synthesis,” IEEE/CVF CVPRW 2025 – IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshop, Nashville, TN, (USA), June 2025 [link][Arxiv].
[P5] M. Pastorino, M. Castiglione, F. Gallo, M. Nigro, N. Sacco, G. Moser “Multisource Fusion of Remote Sensing and Mobility Data for Traffic Analysis Zone Definition,” IGARSS 2025 - IEEE International Geoscience and Remote Sensing Symposium, Brisbane, (Australia), August 2025 [link][HAL link].
[P6] M. Pastorino, M. Alibani, N. Acito, G. Moser “Synthesis of abundance maps through blind hyperspectral unmixing and deep diffusion models,” IGARSS 2025 - IEEE International Geoscience and Remote Sensing Symposium, Brisbane, (Australia), August 2025 [link].
[P7] M. Pastorino, G. Moser, S. B. Serpico, J. Zerubia, “CFC-MCRF: Multiresolution fusion and segmentation of hyperspectral and panchromatic remote sensing images with deep learning and CRFs,” EUSIPCO 2025 – 33rd IEEE European Signal Processing Conference, Palermo, (Italy), September 2025 [link][HAL link].
[P8] M. Alibani, M. Pastorino, G. Moser, N. Acito, “Deep learning for reconstructing hyperspectral VNIR-SWIR data from multispectral sources,” EUSIPCO 2025 – 33rd IEEE European Signal Processing Conference, Palermo, (Italy), September 2025 [link].
[P9] A. La Fata, M. Pastorino, G. Moser, R. Procopio, M. Bernardi, E. Fiori, M. Lagasio, “A Convolutional Recurrent Neural Network to Nowcast Cloud-to-Ground Lightning,” SIPDA 2025 -- XVIII SIPDA International Symposium on Lightning Protection, Thessaloniki, (Greece), September 2025.
2024
[P10] M. Pastorino, G. Moser, F. Guerra, S. B. Serpico, J. Zerubia, “Probabilistic Fusion Framework Combining CNNs and Graphical Models for Multiresolution Satellite and UAV Image Classification,” ICPR 2024 – 27th International Conference on Pattern Recognition, Kolkata, (India), December 2024, doi: 10.1007/978-3-031-78166-7_19 [link] [HAL link].
[P11] M. Pastorino, G. Moser, F. Guerra, S. B. Serpico, and J. Zerubia, “A Multiresolution Fusion Framework based on Probabilistic Graphical Modeling for Burnt zones mapping from satellite and UAV imagery,” IGARSS 2024 - IEEE International Geoscience and Remote Sensing Symposium, Athens, (Greece), July 2024, doi: 10.1109/IGARSS53475.2024.10641389 [link] [HAL link].
2023
[P12] M. Pastorino, G. Moser, S. B. Serpico, and J. Zerubia, “Learning CRF potentials through fully convolutional networks for satellite image semantic segmentation,” SITIS 2023 - International Conference on Signal-Image Technology &Internet-Based Systems, Bangkok, (Thailand), November 2023. doi: 10.1109/SITIS61268.2023.00023 [link] [HAL link].
[P13] M. Pastorino, G. Moser, S. B. Serpico, and J. Zerubia, “Classification of Multimission SAR Images based on Probabilistic Graphical Models and Convolutional Neural Networks,” IGARSS 2023 - IEEE International Geoscience and Remote Sensing Symposium, Pasadena, California, (USA), July 2023. doi: 10.1109/IGARSS52108.2023.10283356 [link] [HAL link].
2022
[P14] M. Pastorino, G. Moser, S. B. Serpico, and J. Zerubia, “Fully convolutional and feedforward networks for the semantic segmentation of remotely sensed images,” ICIP 2022 - IEEE International Conference in Image Processing, Bordeaux, (France), October 2022, doi: 10.1109/ICIP46576.2022.9897336 [link] [HAL link].
[P15] M. Pastorino, G. Moser, S. B. Serpico, and J. Zerubia, “Semantic segmentation of SAR images through fully convolutional networks and hierarchical probabilistic graphical models,” IGARSS 2022 - IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, (Malaysia), July 2022, doi: 10.1109/IGARSS46834.2022.9883111 [link] [HAL link].
2021
[P16] M. Pastorino, G. Moser, S. B. Serpico, e J. Zerubia, “Hierarchical Probabilistic Graphical Models and Deep Convolutional Neural Networks for Remote Sensing Image Classification,” EUSIPCO 2021 - 29th IEEE European Signal Processing Conference, Dublin, (Ireland), Aug. 2021, doi: 10.23919/EUSIPCO54536.2021.9616179 [link] [HAL link].
[P17] M. Pastorino, G. Moser, S. B. Serpico, and J. Zerubia, “Semantic Segmentation of Remote Sensing Images Combining Hierarchical Probabilistic Graphical Models and Deep Convolutional Neural Networks,” IGARSS 2021 - IEEE International Geoscience and Remote Sensing Symposium, Brussels, (Belgium), July 2021, doi: 10.1109/IGARSS47720.2021.9553253 (First Best Paper Award - Mikio Takagi Student Paper) [link] [HAL link].
2021
[NC1] M. Pastorino, G. Moser, S. B. Serpico, e J. Zerubia, “Segmentation Sémantique d'Images de Télédétection Combinant Modèles Graphiques Probabilistes Hiérarchiques et Réseaux de Neurones Convolutifs Profonds,” ORASIS 2021, Sep 2021, Saint-Ferréol, France. [link HAL]
[T1] M. Pastorino, “Regularization Methods for Image Restoration”, B.Sc. thesis in Electronic Engineering and Information Technology, advisor: Prof. C. Estatico, 2018.
[T2] M. Pastorino, “A Novel Method for Semantic Segmentation of Remote Sensing Images Combining Hierarchical Probabilistic Graphical Models and Deep Convolutional Neural Networks”, M.Sc. thesis in Internet and Multimedia Engineering, University of Genoa, Italy and M.Sc. SISEA, Mathematical and Computational Engineering, IMT Atlantique (Ecole Mines-Télécom), Brest, France, advisors: Prof. G. Moser and Prof. J. Zerubia, October 2020.
[T3] M. Pastorino, “Probabilistic graphical models and deep learning methods for remote sensing image analysis,” Ph.D. thesis is Science and Technologies for Electronic and Telecommunication Engineering (STIET), University of Genoa, Italy, and Ph.D. in Sciences et Technologies de l'Information et de la Communication (STIC), INRIA, Université Côte d’Azur, France, advisors: Prof. G. Moser and Prof. J. Zerubia, Ph.D. program chairmen: Prof. M. Valle (STIET) and Prof. J. P. Comet (STIC), December 2023 [link] [HAL link].