Cloth Combine Estimation System Using Deep Learning;

Abstract

The clothing companies are paying more attention on meeting their customers on digital platforms and perform their marketing over the cloth combines which are created by fashion designers. Moreover, the companies on e- commerce platform use cloth recommendation system to draw their customers attention and perform sales. The customers browsing the e-commerce sites are facing some cloth recommendations based on the statistics such as 'those looking at this product also looked at this product'. However, beside of statistical recommendations, more intelligence is required to recommend the cloth which combines the cloth that customers own or going to own. In this study, a cloth combine completion system is developed for e-commerce. The system is based deep neural network (DNN) and it is intended to imitate the fashion designer of the brands on digital market. The study is performed over the cloth combines shown on the e-commerce site of an international cloth company. In contrast to applications based on image processing, the clothes are parameterized depending on expert knowledge and a deep neural network is trained to find the best bottom clothing to the selected top clothing. Using the trained network, the brands can create user specific cloth combines as if the combines are performed by fashion-designer. © 2020 IEEE.