Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/73725
Title: CLOTHING CLASSIFICATION USING SHALLOW CONVOLUTIONAL NEURAL NETWORKS
Authors: Nguyễn, Thanh Hải
Nguyễn, Lâm Trúc Mai
Keywords: CÔNG NGHỆ THÔNG TIN-CHẤT LƯỢNG CAO
Issue Date: 2021
Publisher: Trường Đại Học Cần Thơ
Abstract: The online fashion industry is continuously growing with more requirements considerably from applications of technologies such as 3D printing, digital clothing, Internet of Things, etc. Many customers expect an algorithm capable of recognizing clothes may help clothing merchants better understand the profile of potential customers, focus sales targeting specific niches, design campaigns based on consumer preferences, and improve user experience. Methods of artificial intelligence that can detect and categorize human clothes are necessary and can increase sales or better understand customers. Recent advancements in deep learning have sparked a slew of computer vision-based commercial applications. Object identification is used in a variety of industries to speed up business processes. Deep learning tools and techniques are used in a variety of ways. One of them is clothing classification in the clothing business. The trained deep learning model can predict the name of any clothing by displaying an image of it, and this process can be repeated at a much quicker pace to tag thousands of items in a short amount of time with high accuracy
Description: 58 Tr
URI: https://dspace.ctu.edu.vn/jspui/handle/123456789/73725
Appears in Collections:Trường Công nghệ Thông tin & Truyền thông

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