본문 바로가기
  • Home

Classification of Tourist Photo for Intelligent Tourism Service

  • Journal of the Korean Cartographic Association
  • Abbr : JKCA
  • 2019, 19(3), pp.87-101
  • Publisher : The Korean Cartographic Association
  • Research Area : Social Science > Geography > Geography in general > Cartography
  • Received : December 15, 2019
  • Accepted : December 24, 2019
  • Published : December 31, 2019

Cho, Nahye 1 Youngok Kang 2 윤지영 3 박소연 3

1이화여자대학교 사회교육과
2이화여자대학교
3일반대학원 사회과교육과 지리학전공

Accredited

ABSTRACT

In recent years technology of Convolutional Neural Network (CNN) among the technologies of deep learning has evolved dramatically and has shown an outstanding performance in the analysis of image data. First of all, the training of deep learning model is prerequisite to classify the photos posted by the tourists on Web by applying CNN technology. In this study we aim to develop the photo classification system in view of travel purpose in order to classify the photos posted by tourists on Flickr. We developed the category for photo classification by reviewing around 38,000 photos posted by tourists as well as by analysing literatures and web sites, and then verified the category by classifying 8,400 photos one by one manually according to the category developed. The category we developed has 3 hierarchical levels such as 13 major classification, 64 medium classification and 164 minor classification. We expect that our study can applied in base material when one tries to classify the photos for travel purpose by using the CNN deep learning model.

Citation status

* References for papers published after 2022 are currently being built.