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http://dx.doi.org/10.9715/KILA.2022.50.6.042

Development of Image Classification Model for Urban Park User Activity Using Deep Learning of Social Media Photo Posts  

Lee, Ju-Kyung (Interdisciplinary Program in Landscape Architecture, Seoul National University)
Son, Yong-Hoon (Graduate School of Environment Studies, Seoul National University)
Publication Information
Journal of the Korean Institute of Landscape Architecture / v.50, no.6, 2022 , pp. 42-57 More about this Journal
Abstract
This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.
Keywords
Convolutional Neural Network (CNN); Computer Vision; Urban Park Evaluation; Patterns of Urban Park Use;
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Times Cited By KSCI : 6  (Citation Analysis)
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