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http://dx.doi.org/10.14702/JPEE.2019.175

Fashion Image Searching Website based on Deep Learning Image Classification  

Lee, Hak-Jae (Computer Science, Korea University of Technology and Education)
Lee, Seok-Jun (Computer Science, Korea University of Technology and Education)
Choi, Moon-Hyuk (Computer Science, Korea University of Technology and Education)
Kim, So-Yeong (Computer Science, Korea University of Technology and Education)
Moon, Il-Young (Computer Science, Korea University of Technology and Education)
Publication Information
Journal of Practical Engineering Education / v.11, no.2, 2019 , pp. 175-180 More about this Journal
Abstract
Existing fashion web sites show only the search results for one type of clothes in items such as tops and bottoms. As the fashion market grows, consumers are demanding a platform to find a variety of fashion information. To solve this problem, we devised the idea of linking image classification through deep learning with a website and integrating SNS functions. User uploads their own image to the web site and uses the deep learning server to identify, classify and store the image's characteristics. Users can use the stored information to search for the images in various combinations. In addition, communication between users can be actively performed through the SNS function. Through this, the plan to solve the problem of existing fashion-related sites was prepared.
Keywords
Computer vision; CNN; Deep learning; Image classification; Web;
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