Abstract
Paper deals with supervised classification approach based on fuzzy sets. The fuzzy approach represents a minor adaptation of supervised fuzzy classification which can be found in [2] and used formerly for speech recognition problems. This method was tested for classification of remotely sensed multi-spectral video imagery. Results of this classification approach seem to be promising in comparison with classical techniques and also with some neuro-fuzzy approaches.
This paper was supported with USA-Slovak grant # 94077, awarded by Slovak-USA International Agency for Science and Technology in 1994. Cooperation is underway with Dr. Howard Veregin from University of Minnesota, USA Co-PI of the project.
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Sinčák, P. (1997). Supervised classification of remotely sensed images based on fuzzy sets. In: Reusch, B. (eds) Computational Intelligence Theory and Applications. Fuzzy Days 1997. Lecture Notes in Computer Science, vol 1226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62868-1_144
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DOI: https://doi.org/10.1007/3-540-62868-1_144
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