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dc.contributor.authorCarrara, Andrea
dc.contributor.authorNousias, Stavros
dc.contributor.authorBorrmann, André
dc.date.accessioned2026-08-20T21:24:09Z
dc.date.available2026-08-20T21:24:09Z
dc.date.copyright2025/07/25
dc.date.issued2025
dc.identifier.otherJCCEE5.CPENG-6508.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314393
dc.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 ...
dc.publisherAmerican Society of Civil Engineers
dc.titleVectorGraphNET: Graph Attention Networks for Accurate Segmentation of Complex Technical Drawings
dc.typeJournal Article
dc.journal.volume39
dc.journal.issue6
dc.journal.titleJournal of Computing in Civil Engineering
dc.identifier.doi10.1061/JCCEE5.CPENG-6508
dc.journal.fristpage04025085-1
dc.journal.lastpage04025085-19
dc.page19
dc.treeJournal of Computing in Civil Engineering:;2025:;Volume ( 039 ):;issue: 006
dc.contenttypeFulltext


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