Expertises
Earth & Environmental Sciences
# Detection
# Imagery
# Informal Settlement
# Learning
# Remote Sensing
Engineering & Materials Science
# Deep Learning
# Remote Sensing
# Unmanned Aerial Vehicles (Uav)
Verbonden aan
Publicaties
Recent
Zhou, W.
, Persello, C., Li, M.
, & Stein, A. (2023).
Building use and mixed-use classification with a transformer-based network fusing satellite images and geospatial textual information.
Remote sensing of environment,
297, [113767].
https://doi.org/10.1016/j.rse.2023.113767
Kumar, V., Venkatachalaperumal, S. R.
, & Persello, C. (2023).
Synergistic fusion of spaceborne polarimetric SAR and hyperspectral data for land cover classification. In S. Kumar, P. Siqueira, H. Govil, & S. Agrawal (Eds.),
Spaceborne Synthetic Aperture Radar Remote Sensing: Techniques and Applications (pp. 169-210). CRC Press/Balkema.
https://doi.org/10.1201/9781003204466-8
Persello, C., Hansch, R., Vivone, G., Chen, K., Yan, Z., Tang, D., Huang, H., Schmitt, M., & Sun, X. (2023).
2023 IEEE GRSS data fusion contest: Large-scale fine-grained building classification for semantic urban reconstruction [technical committees].
IEEE geoscience and remote sensing magazine,
11(1), 94-97.
https://doi.org/10.1109/MGRS.2023.3240233
Lv, X.
, Persello, C.
, Zhao, W., Huang, X., Hu, Z., Ming, D.
, & Stein, A. (2023).
Pruning for image segmentation: Improving computational efficiency for large-scale remote sensing applications.
ISPRS journal of photogrammetry and remote sensing,
202, 13-29.
https://doi.org/10.1016/j.isprsjprs.2023.05.024
Zhou, W.
, Persello, C.
, & Stein, A. (2023).
Building usage classification using a transformer-based multimodal deep learning method. In
2023 Joint Urban Remote Sensing Event, JURSE 2023 (2023 Joint Urban Remote Sensing Event, JURSE 2023). IEEE.
https://doi.org/10.1109/JURSE57346.2023.10144168
Zhao, W.
, Persello, C., Ding, H.
, & Stein, A. (2023).
Learning general representations for semantic segmentation and height estimation from remote sensing images. In
2023 Joint Urban Remote Sensing Event (2023 Joint Urban Remote Sensing Event, JURSE 2023). IEEE.
https://doi.org/10.1109/JURSE57346.2023.10144138
Grift, J.
, Persello, C.
, & Koeva, M. N. (2023).
Cadastral boundary delineation using deep learning and remote sensing imagery: state of the art and future developments. In
FIG Working Week 2023: Protecting Our World, Conquering New Frontiers International Federation of Surveyors (FIG).
https://fig.net/fig2023/technical_program.htm
Zhao, W.
, Persello, C.
, & Stein, A. (2023).
Semantic-aware unsupervised domain adaptation for height estimation from single-view aerial images.
ISPRS journal of photogrammetry and remote sensing,
196, 372-385.
https://doi.org/10.1016/j.isprsjprs.2023.01.003
Hansch, R.
, Persello, C., Vivone, G., Castillo Navarro, J., Boulch, A., Lefevre, S., & Le Saux, B. (2022).
Report on the 2022 IEEE Geoscience and Remote Sensing Society Data Fusion Contest: Semisupervised learning.
IEEE geoscience and remote sensing magazine, 2-5.
https://doi.org/10.1109/MGRS.2022.3219935
Zhao, W. (2022).
Extracting geometric features of buildings from remote sensing images. [PhD Thesis - Research UT, graduation UT, Faculty of Geo-Information Science and Earth Observation, University of Twente]. University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC).
https://doi.org/10.3990/1.9789036554978
Koeva, M. N., Bennett, R. M.
, & Persello, C. (2022).
Remote sensing for land administration 2.0.
Remote sensing,
14(17), [4359].
https://doi.org/10.3390/rs14174359
Farsad Layegh, N.
, Darvishzadeh, R.
, Skidmore, A. K.
, Persello, C., & Kruger, N. (2022).
Integrating semi-supervised learning with an expert system for vegetation cover classification using Sentinel-2 and RapidEye data.
Remote sensing,
14(15), 1-18. [3605].
https://doi.org/10.3390/rs14153605
Zhao, W.
, Persello, C.
, & Stein, A. (2022).
Extracting planar roof structures from very high resolution images using graph neural networks.
ISPRS journal of photogrammetry and remote sensing,
187, 34-45.
https://doi.org/10.1016/j.isprsjprs.2022.02.022
Hänsch, R.
, Persello, C., Vivone, G., Castillo Navarro, J., Boulch, A., Lefevre, S., & Le Saux, B. (2022).
The 2022 IEEE GRSS data fusion contest: Semisupervised learning [technical committees].
IEEE geoscience and remote sensing magazine,
10(1), 334-337.
https://doi.org/10.1109/MGRS.2022.3144291
Persello, C., Wegner, J. D., Hansch, R., Tuia, D., Ghamisi, P.
, Koeva, M., & Camps-Valls, G. (2022).
Deep learning and earth observation to support the sustainable development goals: Current approaches, open challenges, and future opportunities.
IEEE geoscience and remote sensing magazine,
10(2), 172-200.
https://doi.org/10.1109/MGRS.2021.3136100
Nex, F., Armenakis, C., Cramer, M., Cucci, D. A., Gerke, M., Honkavaara, E., Kukko, A.
, Persello, C., & Skaloud, J. (2022).
UAV in the advent of the twenties: Where we stand and what is next.
ISPRS journal of photogrammetry and remote sensing,
184, 215-242.
https://doi.org/10.1016/j.isprsjprs.2021.12.006
Kuffer, M., Grippa, T.
, Persello, C., Taubenböck, H.
, Pfeffer, K.
, & Sliuzas, R. (2022).
Mapping the morphology of urban deprivation. In X. Yang (Ed.),
Urban Remote Sensing: Monitoring, Synthesis, and Modeling in the Urban Environment (pp. 305-323). Wiley.
https://doi.org/10.1002/9781119625865.ch14
Mullissa, A. G.
, Persello, C., & Reiche, J. (2022).
Despeckling polarimetric SAR data using a multistream complex-valued fully convolutional network.
IEEE geoscience and remote sensing letters,
19, 1-5.
https://doi.org/10.1109/LGRS.2021.3066311
Zhao, W.
, Persello, C.
, & Stein, A. (2021).
End-to-end roofline extraction from very-high-resolution remote sensing images. In
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS (pp. 2783-2786). IEEE.
https://doi.org/10.1109/IGARSS47720.2021.9554162
Sun, X.
, Zhao, W.
, V. Maretto, R.
, & Persello, C. (2021).
Building polygon extraction from aerial images and digital surface models with a frame field learning framework.
Remote sensing,
13(22), 1-21. [4700].
https://doi.org/10.3390/rs13224700
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Vakken Collegejaar 2023/2024
Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.
Vakken Collegejaar 2022/2023
Contactgegevens
Bezoekadres
Universiteit Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds
(gebouwnr. 19), kamer 1324
Hallenweg 8
7522NH Enschede
Postadres
Universiteit Twente
Faculty of Geo-Information Science and Earth Observation
Langezijds
1324
Postbus 217
7500 AE Enschede