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    Detecting and Locating Multiple Pavement Distresses Using Weakly Supervised Learning Methods

    Source: Journal of Transportation Engineering, Part B: Pavements:;2026:;Volume ( 152 ):;issue: 002::page 04026016-1
    Author:
    Sirhan, Mai
    ,
    Bekhor, Shlomo
    ,
    Sidess, Arieh
    DOI: 10.1061/JPEODX.PVENG-1886
    Publisher: American Society of Civil Engineers
    Abstract: AbstractPavement management and rehabilitation systems require reliable detection and assessment of road pavement distresses. Traditional methods that rely on visual inspections and manual surveys are time-consuming and inconsistent. Several computer ...Practical ApplicationsMaintaining roads in good condition is essential for safe and cost-effective transportation. Traditional methods for identifying pavement damage rely on visual inspection or complex models that need large amounts of detailed, ...
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      Detecting and Locating Multiple Pavement Distresses Using Weakly Supervised Learning Methods

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4313008
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    contributor authorSirhan, Mai
    contributor authorBekhor, Shlomo
    contributor authorSidess, Arieh
    date accessioned2026-08-20T12:02:16Z
    date available2026-08-20T12:02:16Z
    date copyright2026/03/24
    date issued2026
    identifier otherJPEODX.PVENG-1886.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4313008
    description abstractAbstractPavement management and rehabilitation systems require reliable detection and assessment of road pavement distresses. Traditional methods that rely on visual inspections and manual surveys are time-consuming and inconsistent. Several computer ...Practical ApplicationsMaintaining roads in good condition is essential for safe and cost-effective transportation. Traditional methods for identifying pavement damage rely on visual inspection or complex models that need large amounts of detailed, ...
    publisherAmerican Society of Civil Engineers
    titleDetecting and Locating Multiple Pavement Distresses Using Weakly Supervised Learning Methods
    typeJournal Article
    journal volume152
    journal issue2
    journal titleJournal of Transportation Engineering, Part B: Pavements
    identifier doi10.1061/JPEODX.PVENG-1886
    journal fristpage04026016-1
    journal lastpage04026016-13
    page13
    treeJournal of Transportation Engineering, Part B: Pavements:;2026:;Volume ( 152 ):;issue: 002
    contenttypeFulltext
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