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Applying novelty detection to identify model element to IFC class misclassifications on architectural and infrastructure Building Information Models

Article ID Journal Published Year Pages File Type
10151247 Journal of Computational Design and Engineering 2018 48 Pages PDF
Keywords
AIATNRAECMVDNIBSCICACCIFCNovelty detectionAccuracyTPRLodSVMSupport vector machinesBuilding Information ModelingBIMTrue positive rateTrue negative rateOne-class SVMIndustry Foundation ClassesSTEP
Related Topics
Physical Sciences and Engineering Computer Science Computer Graphics and Computer-Aided Design
Preview
Applying novelty detection to identify model element to IFC class misclassifications on architectural and infrastructure Building Information Models
Authors
Bonsang Koo, Byungjin Shin,
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Journal
Journal of Computational Design and Engineering
Journal: Journal of Computational Design and Engineering
Related Categories
AIA
TNR
AEC
MVD
NIBS
CIC
ACC
IFC
Novelty detection
Accuracy
TPR
Lod
SVM
Support vector machines
Building Information Modeling
BIM
True positive rate
True negative rate
One-class SVM
Industry Foundation Classes
STEP
Artificial Intelligence
Computational Theory and Mathematics
Computer Graphics and Computer-Aided Design
Computer Networks and Communications
Computer Science (General)
Computer Science Applications
Computer Vision and Pattern Recognition
Hardware and Architecture
Human-Computer Interaction
Information Systems
Signal Processing
Software
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