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Talks
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Here you can find presentations given at various international conferences.
2013
- D. Tuia, M. Volpi, M. dalla Mura, A. Rakotomamonjy, and R. Flamary. Create the relevant spatial filterbank in the hyperspectral jungle. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Melbourne, Australia, 2013.
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D. Tuia, M. Trolliet, and M. Volpi. Multisource alignment of image manifolds. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Melbourne, Australia, 2013.
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M. Volpi, F. De Morsier, G. Camps-Valls, Kanevski M., and D. Tuia. Multisensor change detection with nonlinear canonical correlation. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Melbourne, Australia, 2013.
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J. P. Jacobs, G. Thoonen, D. Tuia, G. Camps-Valls, B. Haest, and P. Scheunders. Domain adaptation with hidden Markov random fields. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Melbourne, Australia, 2013.
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G. Matasci, N. Longbotham, F. Pacifici, Kanevski M., and D. Tuia. Statistical assessment of dataset shift in model portability of multi-angle image acquisitions. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Melbourne, Australia, 2013.
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M. Volpi, G. Matasci, Kanevski M., and D. Tuia. Multi-view feature extraction for hyperspectral image classification. In European Symposium on Artificial Neural Networks ESANN, Bruges, Belgium, 2013.
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M. Trolliet, M. Volpi, and D. Tuia. Classification of urban multi-angular image sequences by aligning their manifolds. In Joint Urban Remote Sensing Event, Sao Paulo, Brazil, 2013.
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G. Matasci, L. Bruzzone, M. Volpi, D. Tuia, and Kanevski M. Investigating the feature extrac- tion framework for domain adaptation in remote sensing image classification. In International Conference on Pattern Recognition Applications and Methods (ICPRAM), Barcelona, Spain, 2013.
2012
- D. Tuia, M. Volpi, M. dalla Mura, A. Rakotomamonjy, and R. Flamary. Discovering relevant spatial filterbanks for VHR image classification. In Int. Conf. Pattern Recognition (ICPR), Tokyo, Japan, 2012.
- F. De Morsier, D. Tuia, M. Borgeaud, G. Volker, and J.-P. Thiran. Unsupervised changed detection via hierarchical support vector clustering. In Int. Conf. Pattern Recognition (ICPR), Workshop Pattern Recognition in Remote Sensing (PRRS), Tokyo, Japan, 2012.
- D. Tuia, A. Pozdnoukhov, and M. Kanevski. Using active learning for monitoring networks design: the example of wind power plants sites evaluation. In 9th International Geostatistics Congress, Oslo, Norway, 2012.
- V. Laparra, D. Tuia, S. Jímenez, G. Camps-Valls, and J. Malo. Nonlinear data description with principal polynomial analysis. In IEEE Machine Learning for Signal Processing Workshop, Santander, Spain, 2012.
- D. Tuia and J. Muñoz-Marí. Putting the user into the active learning loop: towards realistic but efficient photointerpretation. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Munich, Germany, 2012.
- M. Volpi, G. Matasci, Tuia D., and M. Kanevski. Enhanced change detection using nonlinear feature extraction. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Munich, Germany, 2012.
- M. Furlani, D. Tuia, J. Muñoz-Marí, F. Bovolo, G. Camps-Valls, and L. Bruzzone. Discovering single classes in remote sensing images with active learning. In IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Munich, Germany, 2012.
2011
- D. Tuia, S. Joost, and A. Pozdnoukhov. Active multiple kernel learning of wind power resources. In Machine Learning for Sustainability, NIPS Workshop, Granada, Spain, 2011. [Paper]
Note concerning publications: This material is presented to ensure timely dissemination of scholarly and technical work related to the SNSF project PZ00P2_136827. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
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