2 March 1994 Experiences from operational cloud classifier based on self-organizing map
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Abstract
A new operational system to interpret satellite images is represented. The described method is adaptive. It is trained by examples. In the reported application a combination of textural and spectral measures is used as a feature vector. The adaptation or learning of the extracted feature vectors occurs by a self-organizing process. As a result a topological feature map is generated. The map is identified by known samples, examples of clouds. The map is used later on as a code book for cloud classification. The obtained verification results are good. The represented method is general in the sense that by reselecting features it can be applied to new problems.
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Ari J. E. Visa, Ari J. E. Visa, K. Valkealahti, K. Valkealahti, Jukka Iivarinen, Jukka Iivarinen, O. Simula, O. Simula, } "Experiences from operational cloud classifier based on self-organizing map", Proc. SPIE 2243, Applications of Artificial Neural Networks V, (2 March 1994); doi: 10.1117/12.169997; https://doi.org/10.1117/12.169997
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