Classification of architectural designs using Deep Learning
Devaiah KN1, Anita HB2
1Devaiah K. N., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India.
2Anita H. B., Associate Professor, Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India
Manuscript received on January 26, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 2471-2474 | Volume-9 Issue-3, February 2020. | Retrieval Number: C5621029320/2020©BEIESP | DOI: 10.35940/ijeat.C5621.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Architecture style of buildings play’s an important role in various aspects. Architectural style or the construction method affects the human health in multiple ways. Many dynasties are ruled India and constructed various types of monuments. So, In this proposed work popular dynasties like Hoysala dynasty, Vijayanagar empire, Mughal empire, Nizam’s of Hyderabad, Chalukya dynasty etc. are considered for creating dataset for the work. The architects of those times had really good knowledge about the different scientific methods to be used for construction. This project aims at classification of different architectural styles. Automatic identification of different architectural styles would facilitate different applications. The dataset is manually created by downloading images from various websites. Deep learning, inception v3 master algorithm are used. Experiments are performed using tenser flow and bottle neck files are created for validation. Good recognition rate is achieved with a fewer data set.
Keywords: Dynasty, Inception v3, Architecture, Deep Learning, Convolution Neural Network.