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    Dual-Modal Feature Learning Approach for Probabilistic Semisupervised Interpretation of Subsurface Stratigraphy from Sparse Boreholes and Cone Penetration Tests

    Source: Journal of Geotechnical and Geoenvironmental Engineering:;2026:;Volume ( 152 ):;issue: 003::page 04026001-1
    Author:
    Qian, Zehang
    ,
    Shi, Chao
    ,
    Lee, Siew-Wei
    DOI: 10.1061/JGGEFK.GTENG-14409
    Publisher: American Society of Civil Engineers
    Abstract: AbstractProbabilistic interpretation of subsurface stratigraphy from sparse boreholes and cone penetration tests (CPTs) remains a critical yet nontrivial task in geotechnical site characterization. The challenge primarily arises from three key factors: (1)...
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      Dual-Modal Feature Learning Approach for Probabilistic Semisupervised Interpretation of Subsurface Stratigraphy from Sparse Boreholes and Cone Penetration Tests

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4311523
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    contributor authorQian, Zehang
    contributor authorShi, Chao
    contributor authorLee, Siew-Wei
    date accessioned2026-08-20T10:58:39Z
    date available2026-08-20T10:58:39Z
    date copyright2026/01/05
    date issued2026
    identifier otherJGGEFK.GTENG-14409.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311523
    description abstractAbstractProbabilistic interpretation of subsurface stratigraphy from sparse boreholes and cone penetration tests (CPTs) remains a critical yet nontrivial task in geotechnical site characterization. The challenge primarily arises from three key factors: (1)...
    publisherAmerican Society of Civil Engineers
    titleDual-Modal Feature Learning Approach for Probabilistic Semisupervised Interpretation of Subsurface Stratigraphy from Sparse Boreholes and Cone Penetration Tests
    typeJournal Article
    journal volume152
    journal issue3
    journal titleJournal of Geotechnical and Geoenvironmental Engineering
    identifier doi10.1061/JGGEFK.GTENG-14409
    journal fristpage04026001-1
    journal lastpage04026001-19
    page19
    treeJournal of Geotechnical and Geoenvironmental Engineering:;2026:;Volume ( 152 ):;issue: 003
    contenttypeFulltext
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