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번호 | 참고문헌 | 국회도서관 소장유무 |
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1 | Development of an object model for automated compliance checking | 미소장 |
2 | Automated construction progress measurement using a 4D building information model and 3D data | 미소장 |
3 | Areas of Application for 3D and 4D Models on Construction Projects | 미소장 |
4 | The use of a virtual building design and construction model for developing an effective project concept in 5D environment | 미소장 |
5 | Formalized knowledge of construction sequencing for visual monitoring of work-in-progress via incomplete point clouds and low-LoD 4D BIMs | 미소장 |
6 | A Proposal for Using BIM Model Created in Design to Construction Phase - Case Study on preconstruction adopting BIM - | 미소장 |
7 | Implementation of an interoperable process to optimise design and construction phases of a residential building: A BIM Pilot Project | 미소장 |
8 | A novel selective disassembly sequence planning method for adaptive reuse of buildings | 미소장 |
9 | Spatial Parameterization of Non-Semantic CAD Elements for Supporting Automated Disassembly Planning | 미소장 |
10 | PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space | 미소장 |
11 | Limitation Factors of Building Information Modeling (BIM) Implementation | 미소장 |
12 | A selective disassembly multi-objective optimization approach for adaptive reuse of building components | 미소장 |
13 | BIM-based immersive Virtual Reality for construction workspace planning: A safety-oriented approach | 미소장 |
14 | Automated bridge component recognition from point clouds using deep learning | 미소장 |
15 | SEMANTIC SEGMENTATION OF POINT CLOUDS WITH POINTNET AND KPCONV ARCHITECTURES APPLIED TO RAILWAY TUNNELS | 미소장 |
16 | Automatic Bridge Design Parameter Extraction for Scan-to-BIM | 미소장 |
17 | A Review on Deep Learning Techniques for 3D Sensed Data Classification | 미소장 |
18 | Automatic classification of wall and door BIM element subtypes using 3D geometric deep neural networks | 미소장 |
19 | Automatic Classification of Bridge Component based on Deep Learning | 미소장 |
20 | Automated Construction Progress Management Using Computer Vision-based CNN Model and BIM | 미소장 |
21 | Automatic segmentation and classification of BIM elements from point clouds | 미소장 |
22 | Structure for the classification of disassembly applied to BIM models. | 미소장 |
23 | A framework for BIM-based disassembly models to support reuse of building components | 미소장 |
24 | Integrated BIM-based simulation for automated time-space conflict management in construction projects | 미소장 |
25 | Automated recognition and measurement based on three-dimensional point clouds to connect precast concrete components | 미소장 |
26 | Check and Validation of Building Information Models in Detailed Design Phase: A Check Flow to Pave the Way for BIM Based Renovation and Construction Processes | 미소장 |
27 | Model Validation for Automated Building Code Compliance Checking | 미소장 |
28 | Point cloud semantic segmentation of complex railway environments using deep learning | 미소장 |
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도서위치안내: 정기간행물실(524호) / 서가번호: 국내18
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