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Claudio Persello
Claudio Persello
University of Twente
Bestätigte E-Mail-Adresse bei utwente.nl - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
4092016
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
3422010
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
1652017
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
1642014
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
1612009
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
1572009
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
1422012
Detection of informal settlements from VHR images using convolutional neural networks
N Mboga, C Persello, JR Bergado, A Stein
Remote sensing 9 (11), 1106, 2017
1212017
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
1202015
Delineation of agricultural fields in smallholder farms from satellite images using fully convolutional networks and combinatorial grouping
C Persello, VA Tolpekin, JR Bergado, RA De By
Remote sensing of environment 231, 111253, 2019
1172019
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
1102009
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
922017
UAV in the advent of the twenties: Where we stand and what is next
F Nex, C Armenakis, M Cramer, DA Cucci, M Gerke, E Honkavaara, ...
ISPRS journal of photogrammetry and remote sensing 184, 215-242, 2022
852022
The scope of earth-observation to improve the consistency of the SDG slum indicator
M Kuffer, J Wang, M Nagenborg, K Pfeffer, D Kohli, R Sliuzas, C Persello
ISPRS international journal of geo-information 7 (11), 428, 2018
832018
Building outline delineation: From aerial images to polygons with an improved end-to-end learning framework
W Zhao, C Persello, A Stein
ISPRS journal of photogrammetry and remote sensing 175, 119-131, 2021
782021
Delineation of agricultural field boundaries from Sentinel-2 images using a novel super-resolution contour detector based on fully convolutional networks
KM Masoud, C Persello, VA Tolpekin
Remote sensing 12 (1), 59, 2019
722019
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
722018
The temporal dynamics of slums employing a CNN-based change detection approach
R Liu, M Kuffer, C Persello
Remote sensing 11 (23), 2844, 2019
712019
Machine learning-based slum mapping in support of slum upgrading programs: The case of Bandung City, Indonesia
G Leonita, M Kuffer, R Sliuzas, C Persello
Remote sensing 10 (10), 1522, 2018
712018
Interactive Domain Adaptation for the Classification of Remote Sensing Images Using Active Learning
C Persello
IEEE Geoscience and Remote Sensing Letters, 1-5, 2013
662013
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