심층 전이 학습을 이용한 이미지 검색의 문화적 특성 분석

• Published in: 한국정보통신학회논문지 Vol. 24; no. 5; pp. 674 - 677
• Main Authors: Kim, Hyeon-sik, Jeong, Jin-Woo
• Format: Journal Article
• Language: Korean
• Published: 한국정보통신학회 2020
• Subjects: 전자/정보통신공학; Transfer Learning; Cultural Difference; Deep Learning; Image Search
• ISSN: 2234-4772; 2288-4165
• DOI: 10.6109/jkiice.2020.24.5.674

The cultural background of users utilizing image search engines has a significant impact on the satisfaction of the search results. Therefore, it is important to analyze and understand the cultural context of images for more accurate image search. In this paper, we investigate how the cultural context of images can affect the performance of image classification. To this end, we first collected various types of images (e.g,. food, temple, etc.) with various cultural contexts (e.g., Korea, Japan, etc.) from web search engines. Afterwards, a deep transfer learning approach using VGG19 and MobileNetV2 pre-trained with ImageNet was adopted to learn the cultural features of the collected images. Through various experiments we show the performance of image classification can be differently affected according to the cultural context of images.