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All Journal Journal of Advanced Technology and Multidiscipline (JATM)
Ergidya Liviani
Universitas Airlangga
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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Image Classification on Fashion Dataset Using Inception V3 Maryamah; Najma Attaqiyah Alya; Muhammad Hanif Sudibyo; Ergidya Liviani; Razim Isyraq Thirafi
Journal of Advanced Technology and Multidiscipline Vol. 2 No. 1 (2023): Journal of Advanced Technology and Multidiscipline
Publisher : Faculty of Advanced Technology and Multidiscipline Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jatm.v2i1.44131

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.
Co-Authors Maryamah Muhammad Hanif Sudibyo Najma Attaqiyah Alya Razim Isyraq Thirafi