| Record number | 566220 |
|---|---|
| Title | Improving active learning methods using spatial information |
| Author(s) | Pasolli, Edoardo; Melgani, Farid; Tuia, Devis; Pacifici, Fabio; Emery, William J. |
| Source | In: 2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011 - Proceedings. - - p. 3923 - 3926. |
| Event | 2011 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2011, Vancouver, BC, 2011-07-24/2011-07-29 |
| DOI | https://doi.org/10.1109/IGARSS.2011.6050089 |
| Publication type | Contribution in proceedings |
| Publication year | 2011 |
| Keyword(s) | Active learning - spatial information - support vector machines (SVMs) - very-high-resolution (VHR) images |
| Abstract | Active learning process represents an interesting solution to the problem of training sample collection for the classification of remote sensing images. In this work, we propose a criterion based on the spatial information that can be used in combination with a spectral criterion in order to improve the selection of training samples. Experimental results obtained on a very high resolution image show the effectiveness of regularization in spatial domain and open challenging perspectives for terrain campaigns planning. |
| Comments |
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