Martina Pastorino
Orcid: 0000-0002-3804-4768
According to our database1,
Martina Pastorino
authored at least 13 papers
between 2021 and 2024.
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Bibliography
2024
CRFNet: A Deep Convolutional Network to Learn the Potentials of a CRF for the Semantic Segmentation of Remote Sensing Images.
IEEE Trans. Geosci. Remote. Sens., 2024
Multimission, Multifrequency, and Multiresolution SAR Image Classification Through Hierarchical Markov Models and Convolutional Networks.
IEEE Geosci. Remote. Sens. Lett., 2024
A Multiresolution Fusion Framework based on Probabilistic Graphical Modeling for Burnt Zones Mapping from Satellite and UAV Imagery.
Proceedings of the IGARSS 2024, 2024
2023
Probabilistic graphical models and deep learning methods for remote sensing image analysis.
PhD thesis, 2023
Learning CRF potentials through fully convolutional networks for satellite image semantic segmentation.
Proceedings of the 17th International Conference on Signal-Image Technology & Internet-Based Systems, 2023
Classification of Multimission SAR Images Based on Probabilistic Graphical Models and Convolutional Neural Networks.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023
2022
Semantic Segmentation of Remote-Sensing Images Through Fully Convolutional Neural Networks and Hierarchical Probabilistic Graphical Models.
IEEE Trans. Geosci. Remote. Sens., 2022
Multimodal Fusion of Mobility Demand Data and Remote Sensing Imagery for Urban Land-Use and Land-Cover Mapping.
Remote. Sens., 2022
Semantic Segmentation of SAR Images Through Fully Convolutional Networks and Hierarchical Probabilistic Graphical Models.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022
Fully Convolutional and Feedforward Networks for The Semantic Segmentation of Remotely Sensed Images.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022
2021
Multisensor and Multiresolution Remote Sensing Image Classification through a Causal Hierarchical Markov Framework and Decision Tree Ensembles.
Remote. Sens., 2021
Semantic Segmentation of Remote Sensing Images Combining Hierarchical Probabilistic Graphical Models and Deep Convolutional Neural Networks.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
Hierarchical Probabilistic Graphical Models and Deep Convolutional Neural Networks for Remote Sensing Image Classification.
Proceedings of the 29th European Signal Processing Conference, 2021