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http://dx.doi.org/10.9717/kmms.2022.25.10.1524

A Study on the Classification Model of Minhwa Genre Based on Deep Learning  

Yoon, Soorim (Dept. of Information and Communication Engineering, Dongguk University)
Lee, Young-Suk (Institute of Image and Cultural Contents, Dongguk University)
Publication Information
Journal of Korea Multimedia Society / v.25, no.10, 2022 , pp. 1524-1534 More about this Journal
Abstract
This study proposes the classification model of Minhwa genre based on object detection of deep learning. To detect unique Korean traditional objects in Minhwa, we construct custom datasets by labeling images using object keywords in Minhwa DB. We train YOLOv5 models with custom datasets, and classify images using predicted object labels result, the output of model training. The algorithm consists of two classification steps: 1) according to the painting technique and 2) genre of Minhwa. Through classifying paintings using this algorithm on the Internet, it is expected that the correct information of Minhwa can be built and provided to users forward.
Keywords
Deep Learning; Minhwa; Classification of Minhwa Genre;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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