Implementation of Efficient Inception V2 model for Apparel Counterfeit Detection


Authors : Aditya Umesh Shet; Sheikh Rameez Ibrahim; Mayuri Joshi; Shon Lesly Menezes; Ramalingam H.M

Volume/Issue : Volume 7 - 2022, Issue 4 - April

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3wsYGLw

The problem is, the available technology are does not work to eliminating counterfeit goods. QR codes and holograms are widely used but can be easily duplicated. According to research, the footwear and clothing industry is the industry that has suffered the most losses as a result of counterfeit products. We have seen situations in the Apparel industry where the packaging of counterfeit clothing is as good as the real thing, and this comes as a major concern for brands that provide genuine clothing. So here, we propose a solution that promises to identify counterfeit items on the market using AI and image processing algorithms. In some cases, the acquisition of counterfeit products is a challenge for consumers and can sometimes be dangerous as well. Misconduct of fraudulent practices is most commonly encountered with premium quality products due to its small risk and huge revenue benefits. The counterfeit accessories and actions of counterfeit goods are quickly transformed from mobile marketplace into e-commerce sites. Currently, counterfeit prices of clothing and accessories hinder the financial growth of the luxury goods and the fashion industry. There has been an increase in the adoption of track and trace technology by leading fashion apparel manufacturers around the world. To combat these fraudulent processes, we propose an AI based antifraud system. This study suggests a fraudulent antifraud management system for designer apparels based on AI-based image statistics. This program ensures a complete follow-up of the production of designer clothing. The end user can personally verify the authenticity of the product by sharing the product details in a fixed format.

Keywords : Counterfeit; QR code; Apparel Industry; AI;

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Paper Submission Last Date
31 - July - 2022

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