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Classification of bathroom and bedrooms in holiday homes using resnet

Author: 
Mevlüt Kağan BALGA and Fatih BAŞÇİFTÇİ
Subject Area: 
Physical Sciences and Engineering
Abstract: 

People live in houses with different characteristics due to climate, topography and other factors, or are temporarily accommodated in different types of houses due to holiday. These differences, price, size, hardware, type and so on. many parameters. Nowadays, these houses are temporarily rented because of holiday, they are called holiday homes and can be easily rented through various booking portals. Large booking portals use a variety of artificial intelligence applications to assist customers and landlords. The classification of rooms in holiday homes of different types and configurations can also be considered in these applications. In this study, bathrooms and bedrooms in holiday homes were classified using ResNet deep learning network. In the study, a data set containing a total of 20,000 data unique to a reservation portal operating in Europe was used. For the test and validation, a data set consisting of a total of 10,000 data and totally obtained from Flickr was preferred. As a result of the study, 99.55% accuracy rate was obtained.

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