Open AccessDeep Neural Network for Product Classification System with Korean Character Image
Author(s) -
Jae-Kyung Sung,
Sang-Min Park,
Sang-Yun Sin,
Yung Bok Kim
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.33.21008
Subject(s) - hangul , character (mathematics) , computer science , product (mathematics) , artificial intelligence , artificial neural network , convolutional neural network , deep learning , information retrieval , natural language processing , database , speech recognition , mathematics , geometry
This paper proposes a product classification system based on deep learning using Korean character images (Hangul) to search for products in the shopping mall. Generally, an online shopping mall customer searches through a category classification or a product name to purchase a product. When the exact product name or category is not clear, the user has to search its name. However, the product image classification is degraded because the product logos and characters in the package often interfere. To solve such problems, we propose a classification system based on Deep Learning using Korean character images. The learning data of this system uses Korean character images of PHD08, a Hangul (Korean-language) database. The experimental is carried out using product names collected on the web. For the performance experiment, 10 categories of online shopping mall are selected and the classification accuracy is measured and compared with the previous systems.