Raffaele Gaetano
Raffaele Gaetano
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Zitiert von
Zitiert von
Land cover classification via multitemporal spatial data by deep recurrent neural networks
D Ienco, R Gaetano, C Dupaquier, P Maurel
IEEE Geoscience and Remote Sensing Letters 14 (10), 1685-1689, 2017
Combining Sentinel-1 and Sentinel-2 Satellite Image Time Series for land cover mapping via a multi-source deep learning architecture
D Ienco, R Interdonato, R Gaetano, DHT Minh
ISPRS Journal of Photogrammetry and Remote Sensing 158, 11-22, 2019
A CNN-based fusion method for feature extraction from sentinel data
G Scarpa, M Gargiulo, A Mazza, R Gaetano
Remote Sensing 10 (2), 236, 2018
DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn
R Interdonato, D Ienco, R Gaetano, K Ose
ISPRS journal of photogrammetry and remote sensing 149, 91-104, 2019
Marker-controlled watershed-based segmentation of multiresolution remote sensing images
R Gaetano, G Masi, G Poggi, L Verdoliva, G Scarpa
IEEE Transactions on Geoscience and Remote Sensing 53 (6), 2987-3004, 2014
Deep recurrent neural networks for winter vegetation quality mapping via multitemporal SAR Sentinel-1
DHT Minh, D Ienco, R Gaetano, N Lalande, E Ndikumana, F Osman, ...
IEEE Geoscience and Remote Sensing Letters 15 (3), 464-468, 2018
: A Deep Learning Architecture for Multiscale Multimodal Multitemporal Satellite Data Fusion
P Benedetti, D Ienco, R Gaetano, K Ose, RG Pensa, S Dupuy
IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2018
Hierarchical texture-based segmentation of multiresolution remote-sensing images
R Gaetano, G Scarpa, G Poggi
IEEE Transactions on geoscience and remote sensing 47 (7), 2129-2141, 2009
Hierarchical multiple Markov chain model for unsupervised texture segmentation
G Scarpa, R Gaetano, M Haindl, J Zerubia
IEEE Transactions on Image Processing 18 (8), 1830-1843, 2009
A two-branch CNN architecture for land cover classification of PAN and MS imagery
R Gaetano, D Ienco, K Ose, R Cresson
Remote Sensing 10 (11), 1746, 2018
Detection of environmental hazards through the feature-based fusion of optical and SAR data: A case study in southern Italy
A Errico, CV Angelino, L Cicala, G Persechino, C Ferrara, M Lega, ...
International Journal of Remote Sensing 36 (13), 3345-3367, 2015
Land cover mapping using Sentinel‐2 images and the semi‐automatic classification plugin: A Northern Burkina Faso case study
L Leroux, L Congedo, B Bellón, R Gaetano, A Bégué
QGIS and Applications in Agriculture and Forest 2, 119-151, 2018
Fast super-resolution of 20 m Sentinel-2 bands using convolutional neural networks
M Gargiulo, A Mazza, R Gaetano, G Ruello, G Scarpa
Remote Sensing 11 (22), 2635, 2019
Optical-driven nonlocal SAR despeckling
L Verdoliva, R Gaetano, G Ruello, G Poggi
IEEE Geoscience and Remote Sensing Letters 12 (2), 314-318, 2014
A CNN-based approach for the estimation of canopy heights and wood volume from GEDI waveforms
I Fayad, D Ienco, N Baghdadi, R Gaetano, CA Alvares, JL Stape, ...
Remote Sensing of Environment 265, 112652, 2021
Object-based multi-temporal and multi-source land cover mapping leveraging hierarchical class relationships
YJE Gbodjo, D Ienco, L Leroux, R Interdonato, R Gaetano, B Ndao
Remote Sensing 12 (17), 2814, 2020
Morphological road segmentation in urban areas from high resolution satellite images
R Gaetano, J Zerubia, G Scarpa, G Poggi
2011 17th International Conference on Digital Signal Processing (DSP), 1-8, 2011
A CNN-based fusion method for super-resolution of Sentinel-2 data
M Gargiulo, A Mazza, R Gaetano, G Ruello, G Scarpa
IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018
Weakly supervised learning for land cover mapping of satellite image time series via attention-based CNN
D Ienco, YJE Gbodjo, R Gaetano, R Interdonato
IEEE Access 8, 179547-179560, 2020
Estimating the NDVI from SAR by convolutional neural networks
A Mazza, M Gargiulo, G Scarpa, R Gaetano
IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018
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