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Classification of Building Information Model (BIM) Structures with Deep Learning

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


Original languageEnglish
Title of host publication2018 7th European Workshop on Visual Information Processing (EUVIP)
ISBN (Electronic)978-1-5386-6897-9
ISBN (Print)978-1-5386-6898-6
Publication statusPublished - Nov 2018
Publication typeA4 Article in a conference publication
EventEuropean Workshop on Visual Information Processing -
Duration: 1 Jan 1900 → …

Publication series

ISSN (Electronic)2471-8963


ConferenceEuropean Workshop on Visual Information Processing
Period1/01/00 → …


In this work we study an application of machine learning to the construction industry and we use classical and modern machine learning methods to categorize images of building designs into three classes: Apartment building, Industrial building or Other. No real images are used, but only images extracted from Building Information Model (BIM) software, as these are used by the construction industry to store building designs. For this task, we compared four different methods: the first is based on classical machine learning, where Histogram of Oriented Gradients (HOG) was used for feature extraction and a Support Vector Machine (SVM) for classification; the other three methods are based on deep learning, covering common pre-trained networks as well as ones designed from scratch. To validate the accuracy of the models, a database of 240 images was used. The accuracy achieved is 57% for the HOG + SVM model, and above 89% for the neural networks.

Publication forum classification

Field of science, Statistics Finland