A Fuzzy Rule-Based Feature Construction Approach Applied to Remotely Sensed Imagery
Authors
David García, Dimitris Stavrakoudis, Antonio González, Raúl Pérez, John B. Theocharis
Corresponding Author
David García
Available Online June 2015.
- DOI
- 10.2991/ifsa-eusflat-15.2015.180How to use a DOI?
- Keywords
- Genetic fuzzy systems, feature construction, land cover classification, remote sensing, high-dimensional classification tasks.
- Abstract
The inherent interpretability properties of fuzzy rule-based classification systems (FRBCSs) are undoubtedly one of their major advantages when compared to conventional black-box classifiers. In this paper we present a preliminary study of how the socalled technique of feature construction can prove useful in the context of land cover classification tasks using remotely sensed imagery. The method is integrated into a previously proposed genetic FRBCS (GFRBCS) and applied in a crop classification task using a multispectral satellite image. The experimental analysis shows that feature construction can effectively identify very useful hidden relationships among the initial variables of the problem.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - David García AU - Dimitris Stavrakoudis AU - Antonio González AU - Raúl Pérez AU - John B. Theocharis PY - 2015/06 DA - 2015/06 TI - A Fuzzy Rule-Based Feature Construction Approach Applied to Remotely Sensed Imagery BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 1274 EP - 1281 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.180 DO - 10.2991/ifsa-eusflat-15.2015.180 ID - García2015/06 ER -