YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    Search 
    •   YE&T Library
    • Search
    •   YE&T Library
    • Search
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Search

    Show Advanced FiltersHide Advanced Filters

    Filters

    Use filters to refine the search results.

    Now showing items 1-2 of 2

    • Relevance
    • Title Asc
    • Title Desc
    • Year Asc
    • Year Desc
    • 5
    • 10
    • 20
    • 40
    • 60
    • 80
    • 100
  • Export
    • CSV
    • RIS
    • Sort Options:
    • Relevance
    • Title Asc
    • Title Desc
    • Issue Date Asc
    • Issue Date Desc
    • Results Per Page:
    • 5
    • 10
    • 20
    • 40
    • 60
    • 80
    • 100

    Investigating the Fidelity of Explainable Artificial Intelligence Methods for Applications of Convolutional Neural Networks in Geoscience 

    Source: Artificial Intelligence for the Earth Systems:;2022:;volume( 001 ):;issue: 004
    Author(s): Antonios Mamalakis; Elizabeth A. Barnes; Imme Ebert-Uphoff
    Publisher: American Meteorological Society
    Abstract: Convolutional neural networks (CNNs) have recently attracted great attention in geoscience because of their ability to capture nonlinear system behavior and extract predictive spatiotemporal patterns. Given their black-box ...
    Request PDF

    This Looks Like That There: Interpretable Neural Networks for Image Tasks When Location Matters 

    Source: Artificial Intelligence for the Earth Systems:;2022:;volume( 001 ):;issue: 003
    Author(s): Elizabeth A. Barnes; Randal J. Barnes; Zane K. Martin; Jamin K. Rader
    Publisher: American Meteorological Society
    Abstract: We develop and demonstrate a new interpretable deep learning model specifically designed for image analysis in Earth system science applications. The neural network is designed to be inherently interpretable, rather than ...
    Request PDF
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     

    Author

    Publisher

    Year

    Type

    Content Type

    Publication Title

    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian