Abstract
The main goal of this work is to improve the automatic interpretation of ocean satellite images. We present a comparative study of different classifiers: Graphic Expert System (GES), ANN-based Symbolic Processing Element (SPE), Hybrid System (ANN – Radial Base Function & Fuzzy System), Neuro-Fuzzy System and Bayesian Network.. We wish to show the utility of hybrid and neuro-fuzzy system in recongnition of oceanic structures. On the other hand, other objective is the feature selection, which is considered a fundamental step for pattern recognition. This paper reports a study of learning Bayesian Network for feature selection [1] in the recognition of oceanic structures in satellite images.
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Piedra, J.A., Guindos, F., Molina, A., Canton, M. (2005). Pattern Recognition in AVHRR Images by Means of Hibryd and Neuro-fuzzy Systems. In: Moreno Díaz, R., Pichler, F., Quesada Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2005. EUROCAST 2005. Lecture Notes in Computer Science, vol 3643. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11556985_48
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DOI: https://doi.org/10.1007/11556985_48
Publisher Name: Springer, Berlin, Heidelberg
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