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A Comparative Study of Two Neural Models for Cloud Screening of Iberian Peninsula Meteosat Images

机译:伊比利亚半岛Meteosat图像云筛选两种神经模型的比较研究

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In this work we make a comparative study of the results obtained in the automatic interpretation of the Iberian Peninsula Meteosat images by means of neural networks techniques, in particular, multi-layer perceptrons and self organizing maps. The interpretation of these images implies their segmentation in the classes SEA (S), LAND (L), LOW CLOUDS (C{sub}L), MIDDLE CLOUDS (C{sub}M), HIGH CLOUDS (C{sub}H), and CLOUDS WITH VERTICAL GROUTH (C{sub}V).
机译:在这项工作中,我们通过神经网络技术,特别是多层的感知和自组织地图自动解释Iberian半岛Meteosat图像的自动解释结果的比较研究。对这些图像的解释意味着它们在类海中的分割,土地(L),低云(C {Sub} L),中云(C {Sub} M),高云(C {Sub} H)和垂直格子(c {sub} v)的云。

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