Claudio Persello
TitleCited byYear
Batch-mode active-learning methods for the interactive classification of remote sensing images
B Demir, C Persello, L Bruzzone
IEEE Transactions on Geoscience and Remote Sensing 49 (3), 1014-1031, 2010
2382010
A novel context-sensitive semisupervised SVM classifier robust to mislabeled training samples
L Bruzzone, C Persello
IEEE Transactions on Geoscience and Remote Sensing 47 (7), 2142-2154, 2009
1342009
A novel approach to the selection of spatially invariant features for the classification of hyperspectral images with improved generalization capability
L Bruzzone, C Persello
IEEE transactions on geoscience and remote sensing 47 (9), 3180-3191, 2009
1222009
Domain adaptation for the classification of remote sensing data: An overview of recent advances
D Tuia, C Persello, L Bruzzone
IEEE geoscience and remote sensing magazine 4 (2), 41-57, 2016
1172016
Active and Semisupervised Learning for the Classification of Remote Sensing Images
C Persello, L Bruzzone
IEEE Transactions on Geoscience and Remote Sensing 52 (11), 6937 - 6956, 2014
1062014
Active learning for domain adaptation in the supervised classification of remote sensing images
C Persello, L Bruzzone
IEEE Transactions on Geoscience and Remote Sensing 50 (11), 4468-4483, 2012
802012
A novel protocol for accuracy assessment in classification of very high resolution images
C Persello, L Bruzzone
IEEE Transactions on Geoscience and Remote Sensing 48 (3), 1232-1244, 2009
702009
Kernel-based domain-invariant feature selection in hyperspectral images for transfer learning
C Persello, L Bruzzone
IEEE transactions on geoscience and remote sensing 54 (5), 2615-2626, 2015
622015
Interactive Domain Adaptation for the Classification of Remote Sensing Images Using Active Learning
C Persello
IEEE Geoscience and Remote Sensing Letters, 1-5, 2013
462013
Deep fully convolutional networks for the detection of informal settlements in VHR images
C Persello, A Stein
IEEE geoscience and remote sensing letters 14 (12), 2325-2329, 2017
402017
Informal settlement classification using point-cloud and image-based features from UAV data
CM Gevaert, C Persello, R Sliuzas, G Vosselman
ISPRS journal of photogrammetry and remote sensing 125, 225-236, 2017
402017
Detection of informal settlements from VHR images using convolutional neural networks
N Mboga, C Persello, J Bergado, A Stein
Remote sensing 9 (11), 1106, 2017
342017
Cost-sensitive active learning with lookahead: Optimizing field surveys for remote sensing data classification
C Persello, A Boularias, M Dalponte, T Gobakken, E Naesset, ...
IEEE Transactions on Geoscience and Remote Sensing 52 (10), 6652-6664, 2014
342014
A novel context-sensitive SVM for classification of remote sensing images
F Bovolo, L Bruzzone, M Marconcini, C Persello
University of Trento, 2006
262006
A novel active learning strategy for domain adaptation in the classification of remote sensing images
C Persello, L Bruzzone
2011 IEEE International Geoscience and Remote Sensing Symposium, 3720-3723, 2011
252011
A deep learning approach to the classification of sub-decimetre resolution aerial images
JR Bergado, C Persello, C Gevaert
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2016
232016
Optimizing multiple kernel learning for the classification of UAV data
C Gevaert, C Persello, G Vosselman
Remote sensing 8 (12), 1025, 2016
212016
Recent trends in classification of remote sensing data: Active and semisupervised machine learning paradigms
L Bruzzone, C Persello
2010 IEEE International Geoscience and Remote Sensing Symposium, 3720-3723, 2010
212010
Active learning for classification of remote sensing images
L Bruzzone, C Persello
2009 IEEE International Geoscience and Remote Sensing Symposium 3, III-693 …, 2009
192009
Recurrent multiresolution convolutional networks for VHR image classification
JR Bergado, C Persello, A Stein
IEEE transactions on geoscience and remote sensing 56 (11), 6361-6374, 2018
162018
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