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sebastiano b. serpico
sebastiano b. serpico
university of genoa italy
在 unige.it 的电子邮件经过验证 - 首页
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引用次数
引用次数
年份
Image fusion techniques for remote sensing applications
G Simone, A Farina, FC Morabito, SB Serpico, L Bruzzone
Information fusion 3 (1), 3-15, 2002
5582002
A new search algorithm for feature selection in hyperspectral remote sensing images
SB Serpico, L Bruzzone
IEEE Transactions on Geoscience and Remote Sensing 39 (7), 1360-1367, 2001
4312001
Partially supervised classification of remote sensing images through SVM-based probability density estimation
P Mantero, G Moser, SB Serpico
IEEE Transactions on geoscience and remote sensing 43 (3), 559-570, 2005
4092005
An iterative technique for the detection of land-cover transitions in multitemporal remote-sensing images
L Bruzzone, SB Serpico
IEEE transactions on geoscience and remote sensing 35 (4), 858-867, 1997
3951997
Generalized minimum-error thresholding for unsupervised change detection from SAR amplitude imagery
G Moser, SB Serpico
IEEE Transactions on Geoscience and Remote sensing 44 (10), 2972-2982, 2006
3932006
A neural-statistical approach to multitemporal and multisource remote-sensing image classification
L Bruzzone, DF Prieto, SB Serpico
IEEE Transactions on Geoscience and remote Sensing 37 (3), 1350-1359, 1999
3441999
New frontiers in spectral-spatial hyperspectral image classification: The latest advances based on mathematical morphology, Markov random fields, segmentation, sparse …
P Ghamisi, E Maggiori, S Li, R Souza, Y Tarablaka, G Moser, A De Giorgi, ...
IEEE geoscience and remote sensing magazine 6 (3), 10-43, 2018
3162018
Land-cover mapping by Markov modeling of spatial–contextual information in very-high-resolution remote sensing images
G Moser, SB Serpico, JA Benediktsson
Proceedings of the IEEE 101 (3), 631-651, 2012
2782012
An extension of the Jeffreys-Matusita distance to multiclass cases for feature selection
L Bruzzone, F Roli, SB Serpico
IEEE Transactions on Geoscience and Remote Sensing 33 (6), 1318-1321, 1995
2531995
Conditional copulas for change detection in heterogeneous remote sensing images
G Mercier, G Moser, SB Serpico
IEEE Transactions on Geoscience and Remote Sensing 46 (5), 1428-1441, 2008
2162008
Combining support vector machines and Markov random fields in an integrated framework for contextual image classification
G Moser, SB Serpico
IEEE Transactions on Geoscience and Remote Sensing 51 (5), 2734-2752, 2012
2132012
Classification of multisensor remote-sensing images by structured neural networks
SB Serpico, F Roli
IEEE Transactions on Geoscience and Remote Sensing 33 (3), 562-578, 1995
2121995
SAR amplitude probability density function estimation based on a generalized Gaussian model
G Moser, J Zerubia, SB Serpico
IEEE transactions on image processing 15 (6), 1429-1442, 2006
1952006
A Markov random field approach to spatio-temporal contextual image classification
F Melgani, SB Serpico
IEEE Transactions on Geoscience and Remote Sensing 41 (11), 2478-2487, 2003
1942003
Extraction of spectral channels from hyperspectral images for classification purposes
SB Serpico, G Moser
IEEE transactions on geoscience and remote sensing 45 (2), 484-495, 2007
1922007
Unsupervised change-detection methods for remote-sensing images
F Melgani, G Moser, SB Serpico
Optical Engineering 41 (12), 3288-3297, 2002
1802002
Dictionary-based stochastic expectation-maximization for SAR amplitude probability density function estimation
G Moser, J Zerubia, SB Serpico
IEEE Transactions on Geoscience and Remote Sensing 44 (1), 188-200, 2005
1472005
An experimental comparison of neural and statistical non-parametric algorithms for supervised classification of remote-sensing images
SB Serpico, L Bruzzone, F Roli
Pattern recognition letters 17 (13), 1331-1341, 1996
1391996
A technique for feature selection in multiclass problems
L Bruzzone, SB Serpico
International Journal of Remote Sensing 21 (3), 549-563, 2000
1302000
Unsupervised change detection from multichannel SAR data by Markovian data fusion
G Moser, SB Serpico
IEEE Transactions on Geoscience and Remote Sensing 47 (7), 2114-2128, 2009
1272009
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