| id |
sigradi2021_146 |
| authors |
Yönder, Veli Mustafa, Dogan, Fehmi and Çavka, Hasan Burak |
| year |
2021 |
| title |
Deciphering and Forecasting Characteristics of Bodrum Houses Using Artificial Intelligence (AI) Approaches |
| source |
Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 241–252 |
| summary |
Computer vision (CV), artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications, which are among the rapidly emerging and growing technologies, have the potential to be effectively used in the fields of architecture and construction. These applications are used not only in the field of architectural design development and construction site tracking but also to analyze and predict the architectural properties of existing buildings and heritage classification. This paper aims to classify and analyze the façades of Bodrum houses by using deep learning models, comprehensive relational database (RDB), and artificial neural network based clustering methods. Through the use of the above-mentioned methods, we managed to cluster Bodrum houses' façade attributes in five groups and testing image classification models in three different classifiers. |
| keywords |
Image processing, Deep learning (DL), Classification, Hierarchical cluster analysis, Artificial neural networks (ANNs) |
| series |
SIGraDi |
| email |
|
| full text |
 file.pdf (1,888,055 bytes) |
| references |
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| last changed |
2022/05/23 12:10 |
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