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• W2045162724 abstract "The goal of this paper is to introduce how to make use of the artificial neural network techniqueto develop a new method which can fast recognize atmospheric profiles' characters from hyperspectralinfrared thermal remote sensing. This technique would accelerate the calculation speed of hyperspectralinfrared atmospheric radiative transfer model (RTM). As the launch of hyperspectral infrared sensors suchas Infrared Atmospheric Sounding Interferometer (IASI), it becomes possible for people to take advantageof the hyperspectral data which contains abundance of precise spectral information, to add constraintconditions for the researches of some physical models. But in practice, normal hyperspectral infraredatmospheric RTM are relatively complex and time costing. The calculation speed of these models is not fastenough to make these models to respond to the variety of atmospheric radiative, or the bright temperaturetimely. Therefore, the practical and effective physical models and research methods, such as the practicalsurface temperate inversion model, couldn't be founded relay on these transfer models. In order to solvethis problem, institutions and researchers around the world have tried some methods to develop the fastcalculation of atmospheric RTM. But these methods still have problems on speed, accuracy and theapplicability for certain sensors." @default.
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• W2045162724 date "2009-10-30" @default.
• W2045162724 modified "2023-09-22" @default.
• W2045162724 title "The fast processing method for the recognition of atmospheric profiles' characters based on artificial neural network" @default.
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• W2045162724 doi "https://doi.org/10.1117/12.829597" @default.
• W2045162724 hasPublicationYear "2009" @default.
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