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    Can We Integrate Spatial Verification Methods into Neural Network Loss Functions for Atmospheric Science? 

    Source: Artificial Intelligence for the Earth Systems:;2022:;volume( 001 ):;issue: 004
    Author(s): Ryan Lagerquist; Imme Ebert-Uphoff
    Publisher: American Meteorological Society
    Abstract: In the last decade, much work in atmospheric science has focused on spatial verification (SV) methods for gridded prediction, which overcome serious disadvantages of pixelwise verification. However, neural networks (NN) ...
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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