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    VectorGraphNET: Graph Attention Networks for Accurate Segmentation of Complex Technical Drawings

    Source: Journal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 006::page 04025085-1
    Author:
    Carrara, Andrea
    ,
    Nousias, Stavros
    ,
    Borrmann, André
    DOI: 10.1061/JCCEE5.CPENG-6508
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThis study introduces a new approach to extracting vector data from technical drawings in Portable Document Format (PDF) format and analyzing them semantically by employing graph attention networks. The proposed method involves converting PDF ...Practical ApplicationsTechnical drawings are essential for communication in the AEC industries; however, manual analysis is often time-consuming and error prone. This study presents an efficient method for automating the segmentation and analysis of ...
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      VectorGraphNET: Graph Attention Networks for Accurate Segmentation of Complex Technical Drawings

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314393
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    • Journal of Computing in Civil Engineering

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    contributor authorCarrara, Andrea
    contributor authorNousias, Stavros
    contributor authorBorrmann, André
    date accessioned2026-08-20T21:24:09Z
    date available2026-08-20T21:24:09Z
    date copyright2025/07/25
    date issued2025
    identifier otherJCCEE5.CPENG-6508.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314393
    description abstractAbstractThis study introduces a new approach to extracting vector data from technical drawings in Portable Document Format (PDF) format and analyzing them semantically by employing graph attention networks. The proposed method involves converting PDF ...Practical ApplicationsTechnical drawings are essential for communication in the AEC industries; however, manual analysis is often time-consuming and error prone. This study presents an efficient method for automating the segmentation and analysis of ...
    publisherAmerican Society of Civil Engineers
    titleVectorGraphNET: Graph Attention Networks for Accurate Segmentation of Complex Technical Drawings
    typeJournal Article
    journal volume39
    journal issue6
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/JCCEE5.CPENG-6508
    journal fristpage04025085-1
    journal lastpage04025085-19
    page19
    treeJournal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 006
    contenttypeFulltext
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