Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385805250> ?p ?o ?g. }
Showing items 1 to 80 of
80
with 100 items per page.
- W4385805250 endingPage "9242" @default.
- W4385805250 startingPage "9242" @default.
- W4385805250 abstract "In recent years, deep learning methods have been used with increasing frequency to solve architectural design problems. This paper aims to study the spatial functional layout of deep learning-assisted generation subway stations. Using the PointNet++ model, the subway station point cloud data are trained and then collected and processed by the author. After training and verification, the following conclusions are obtained: (1) the feasibility of spatial deep learning for construction based on PointNet++ in the form of point cloud data is verified; (2) the effectiveness of PointNet++ for the semantic segmentation and prediction of metro station point cloud information is verified; and (3) the results show that the overall 9:1 training prediction data have 60% + MIOU and 75% + accuracy for 9:1 training prediction data in the space of 20 × 20 × 20 and a block_size of 10.0. This paper combines the deep learning of 3D point cloud data with architectural design, breaking through the original status quo of two-dimensional images as research objects. From the dataset level, the limitation that research objects such as 2D images cannot accurately describe 3D space is avoided, and more intuitive and diverse design aids are provided for architects." @default.
- W4385805250 created "2023-08-15" @default.
- W4385805250 creator A5047552734 @default.
- W4385805250 creator A5069186131 @default.
- W4385805250 creator A5080455258 @default.
- W4385805250 date "2023-08-14" @default.
- W4385805250 modified "2023-09-26" @default.
- W4385805250 title "Research on the Intelligent Auxiliary Design of Subway Station Building Space Based on Deep Learning" @default.
- W4385805250 cites W2737911916 @default.
- W4385805250 cites W2902155426 @default.
- W4385805250 cites W2907548847 @default.
- W4385805250 cites W2908182005 @default.
- W4385805250 cites W2951283094 @default.
- W4385805250 cites W2963073614 @default.
- W4385805250 cites W2963800363 @default.
- W4385805250 cites W2986336497 @default.
- W4385805250 cites W2997994322 @default.
- W4385805250 cites W3099345087 @default.
- W4385805250 cites W3111273223 @default.
- W4385805250 cites W3124216104 @default.
- W4385805250 cites W3167290312 @default.
- W4385805250 cites W3183353052 @default.
- W4385805250 cites W4285068668 @default.
- W4385805250 cites W4285724373 @default.
- W4385805250 cites W4288994050 @default.
- W4385805250 doi "https://doi.org/10.3390/app13169242" @default.
- W4385805250 hasPublicationYear "2023" @default.
- W4385805250 type Work @default.
- W4385805250 citedByCount "0" @default.
- W4385805250 crossrefType "journal-article" @default.
- W4385805250 hasAuthorship W4385805250A5047552734 @default.
- W4385805250 hasAuthorship W4385805250A5069186131 @default.
- W4385805250 hasAuthorship W4385805250A5080455258 @default.
- W4385805250 hasBestOaLocation W43858052501 @default.
- W4385805250 hasConcept C108583219 @default.
- W4385805250 hasConcept C111919701 @default.
- W4385805250 hasConcept C119857082 @default.
- W4385805250 hasConcept C131979681 @default.
- W4385805250 hasConcept C154945302 @default.
- W4385805250 hasConcept C2524010 @default.
- W4385805250 hasConcept C2777210771 @default.
- W4385805250 hasConcept C2778572836 @default.
- W4385805250 hasConcept C28719098 @default.
- W4385805250 hasConcept C33923547 @default.
- W4385805250 hasConcept C41008148 @default.
- W4385805250 hasConcept C79974875 @default.
- W4385805250 hasConcept C89600930 @default.
- W4385805250 hasConceptScore W4385805250C108583219 @default.
- W4385805250 hasConceptScore W4385805250C111919701 @default.
- W4385805250 hasConceptScore W4385805250C119857082 @default.
- W4385805250 hasConceptScore W4385805250C131979681 @default.
- W4385805250 hasConceptScore W4385805250C154945302 @default.
- W4385805250 hasConceptScore W4385805250C2524010 @default.
- W4385805250 hasConceptScore W4385805250C2777210771 @default.
- W4385805250 hasConceptScore W4385805250C2778572836 @default.
- W4385805250 hasConceptScore W4385805250C28719098 @default.
- W4385805250 hasConceptScore W4385805250C33923547 @default.
- W4385805250 hasConceptScore W4385805250C41008148 @default.
- W4385805250 hasConceptScore W4385805250C79974875 @default.
- W4385805250 hasConceptScore W4385805250C89600930 @default.
- W4385805250 hasIssue "16" @default.
- W4385805250 hasLocation W43858052501 @default.
- W4385805250 hasOpenAccess W4385805250 @default.
- W4385805250 hasPrimaryLocation W43858052501 @default.
- W4385805250 hasRelatedWork W2790662084 @default.
- W4385805250 hasRelatedWork W3014300295 @default.
- W4385805250 hasRelatedWork W3015465855 @default.
- W4385805250 hasRelatedWork W4223943233 @default.
- W4385805250 hasRelatedWork W4225161397 @default.
- W4385805250 hasRelatedWork W4312200629 @default.
- W4385805250 hasRelatedWork W4360585206 @default.
- W4385805250 hasRelatedWork W4364306694 @default.
- W4385805250 hasRelatedWork W4380075502 @default.
- W4385805250 hasRelatedWork W4380086463 @default.
- W4385805250 hasVolume "13" @default.
- W4385805250 isParatext "false" @default.
- W4385805250 isRetracted "false" @default.
- W4385805250 workType "article" @default.