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.