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A Study on the Prediction Model for the Development of Vacant Homes Using Deep Learning

In recent years, shifting towards compact city is required in response to the declining population and its corresponding increase in vacant houses. In order to induce the compact city policy, each municipalities need to create policies that advocate efficient use and further manage the development of vacant homes. Here, it is necessary to understand the distribution, parameters quantitatively, and features of vacant homes to conclusively establish countermeasures. Therefore, this research uses image recognition technology to develop a vacant homes prediction model. By using image recognition technology and deep learning, it allows the incorporation of a phenomenon that transcends multiple data. As a result, concluded the legitimacy of parameters such as transportation network distribution, use district distribution, and housing distribution.