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Books and Theses
- 2022
[b1]Luca Maggiolo:
Deep Learning and Advanced Statistical Methods for Domain Adaptation and Classification of Remote Sensing Images. University of Genoa, Italy, 2022
Journal Articles
- 2022
- [j2]Luca Maggiolo
, David Solarna, Gabriele Moser, Sebastiano Bruno Serpico:
Registration of Multisensor Images through a Conditional Generative Adversarial Network and a Correlation-Type Similarity Measure. Remote. Sens. 14(12): 2811 (2022) - [j1]Luca Maggiolo, Diego Marcos, Gabriele Moser, Sebastiano B. Serpico, Devis Tuia:
A Semisupervised CRF Model for CNN-Based Semantic Segmentation With Sparse Ground Truth. IEEE Trans. Geosci. Remote. Sens. 60: 1-15 (2022)
Conference and Workshop Papers
- 2024
- [c7]Ignacio Masari, Luca Maggiolo, Gabriele Moser, Sebastiano B. Serpico:
A Deep Learning Architecture for Unsupervised Feature Extraction from Multimission SAR Time Series. IGARSS 2024: 8383-8387 - 2022
- [c6]David Solarna, Luca Maggiolo, Gabriele Moser, Sebastiano B. Serpico:
A Tiling-Based Strategy for Large-Scale Multisensor Optical-Sar Image Registration. IGARSS 2022: 127-130 - [c5]Mostaan Nabi, Luca Maggiolo, Gabriele Moser, Sebastiano B. Serpico:
A CNN-Transformer Knowledge Distillation for Remote Sensing Scene Classification. IGARSS 2022: 663-666 - [c4]Luca Maggiolo, David Solarna, Gabriele Moser, Sebastiano B. Serpico:
Optical-SAR Decision Fusion with Markov Random Fields for High-Resolution Large-Scale Land Cover Mapping. IGARSS 2022: 5508-5511 - 2021
- [c3]Béatrice Pinel-Puysségur, Luca Maggiolo, Michel Roux, Nicolas Gasnier, David Solarna, Gabriele Moser, Sebastiano B. Serpico, Florence Tupin:
Experimental Comparison of Registration Methods for Multisensor Sar-Optical Data. IGARSS 2021: 3022-3025 - 2020
- [c2]Luca Maggiolo, David Solarna, Gabriele Moser, Sebastiano B. Serpico:
Automatic Area-Based Registration of Optical and SAR Images Through Generative Adversarial Networks and a Correlation-Type Metric. IGARSS 2020: 2089-2092 - 2018
- [c1]Luca Maggiolo, Diego Marcos, Gabriele Moser, Devis Tuia:
Improving Maps from CNNs Trained with Sparse, Scribbled Ground Truths Using Fully Connected CRFs. IGARSS 2018: 2099-2102
Coauthor Index
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