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    Development of a Deep Convolutional Neural Network for the Prediction of Pavement Roughness from 3D Images 

    Source: Journal of Transportation Engineering, Part B: Pavements:;2021:;Volume ( 147 ):;issue: 004:;page 04021048-1
    Author(s): Hossam Abohamer; Mostafa Elseifi; Nirmal Dhakal; Zhongjie Zhang; Christophe N. Fillastre
    Publisher: ASCE
    Abstract: Current roughness prediction models require extensive input data including pavement distress, climatic, and traffic data, which may be difficult to collect. In addition, these models have geographical limitations; therefore, ...
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    Surface Identification of Top-Down, Bottom-Up, and Cement-Treated Reflective Cracks Using Convolutional Neural Network and Artificial Neural Networks 

    Source: Journal of Transportation Engineering, Part B: Pavements:;2021:;Volume ( 147 ):;issue: 001:;page 04020080-1
    Author(s): Nirmal Dhakal; Zia U. A. Zihan; Mostafa A. Elseifi; Momen R. Mousa; Kevin Gaspard; Christophe N. Fillastre
    Publisher: ASCE
    Abstract: Transportation agencies often need to differentiate between top-down and bottom-up cracking in the field to set up an effective and targeted schedule and budget for the repair of these cracks. The objective of this study ...
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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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