TY - GEN
T1 - A Proposal of Classification Model for Kawaii Fashion Styles in Japan Using Deep Learning
AU - Laohakangvalvit, Tipporn
AU - Sripian, Peeraya
AU - Miyatake, Keiko
AU - Ohkura, Michiko
N1 - Funding Information:
Acknowledgments. This work was partially supported by JSPS Grant-in-Aid for Scientific Research (20K12032).
Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - Kawaii is a Japanese cultural uniqueness that attracts attention around the world. It has been considered as an important value that increases impressions on various products such as Hello Kitty. Since 2017, we have conducted our research on fashion and investigate kawaii fashion trends in Japan. Our recent study introduces deep learning as a new approach to classify images of kawaii fashion styles. In this study, we propose to construct a classification model to classify five kawaii fashion styles in our dataset consisting of Classic, Harajuku-type Kawaii, Lolita, Orthodox, and Street, each of which has approximately 100 images. We constructed and compared the classification performance between two deep learning models: color-image model and grayscale-image model. As the results, we clarified that the model trained by color images has high performance especially in classify between the HK and the other four kawaii fashion styles. Our proposed model contributes to future application in the fashion industry as a quantitative method in positioning the style for new kawaii fashion designs.
AB - Kawaii is a Japanese cultural uniqueness that attracts attention around the world. It has been considered as an important value that increases impressions on various products such as Hello Kitty. Since 2017, we have conducted our research on fashion and investigate kawaii fashion trends in Japan. Our recent study introduces deep learning as a new approach to classify images of kawaii fashion styles. In this study, we propose to construct a classification model to classify five kawaii fashion styles in our dataset consisting of Classic, Harajuku-type Kawaii, Lolita, Orthodox, and Street, each of which has approximately 100 images. We constructed and compared the classification performance between two deep learning models: color-image model and grayscale-image model. As the results, we clarified that the model trained by color images has high performance especially in classify between the HK and the other four kawaii fashion styles. Our proposed model contributes to future application in the fashion industry as a quantitative method in positioning the style for new kawaii fashion designs.
KW - Classification
KW - Deep learning model
KW - Fashion
KW - Kawaii
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U2 - 10.1007/978-3-031-05311-5_31
DO - 10.1007/978-3-031-05311-5_31
M3 - Conference contribution
AN - SCOPUS:85133032648
SN - 9783031053108
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 450
EP - 461
BT - Human-Computer Interaction. Theoretical Approaches and Design Methods - Thematic Area, HCI 2022, Held as Part of the 24th HCI International Conference, HCII 2022, Proceedings
A2 - Kurosu, Masaaki
PB - Springer Science and Business Media Deutschland GmbH
T2 - Human Computer Interaction thematic area of the 24th International Conference on Human-Computer Interaction, HCII 2022
Y2 - 26 June 2022 through 1 July 2022
ER -