Abstract
Fashion is a form of self-expression that allows us to be able to manifest our personality and identity more confidently. One of the effects of Covid 19 is the economics of the industry, especially the fashion category as the largest category in the e-commerce industry. However, A large number of categories in each fashion brand allows shop owners to be misclassifications about the placement of items that have nearly the same clothing model. The other problem is sellers uploading pictures of products on the platform for the sale and the consequent manual tagging involved. In this paper, we proposed image classification on the fashion dataset using inception V3. The methodology of this paper consists of scrapping data from the official websites of five famous fashion brands, data preprocessing, and classification with the Inception V3 method. The accuracy and F1-Score values obtained using Inception V3 are 92.86% and 92.85%. The proposed method is the highest result of the comparison method and can differentiate between knitted with a scarf that is difficult to classify when compared to other comparison methods.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Advanced Technology and Multidiscipline
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
