Fake Products Detection Using Machine Learning

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Prof. Shah Saloni Niranjan; Mrs.Kokare.S.A.; Rokade Dnyaneshwari; Avate Rutuja; Taware Sakshi

Fake Products Detection Using Machine Learning

Authors: Prof. Shah Saloni Niranjan, Mrs.Kokare.S.A., Rokade Dnyaneshwari, Avate Rutuja, Taware Sakshi

Unique Paper ID: 180477
Volume: 12
Issue: 1
PageNo: 1670-1673

Keywords: Counterfeit items and logos of image recognition pattern analysis and AI-driven algorithms.

Abstract:
The proliferation of counterfeit products and fraudulent branding presents significant challenges for consumers and businesses alike. The Fake Product & Fake Logo Identification System aims to address these challenges by leveraging advanced machine learning and computer vision techniques to accurately identify counterfeit items and logos. This system employs a combination of image recognition, pattern analysis, and AI-driven algorithms to detect discrepancies between genuine and fake products by analyzing subtle differences in logos, packaging, and design elements. By utilizing a comprehensive database of authentic product images and logos, the system compares and flags anomalies indicative of counterfeiting. The goal is to provide a reliable, scalable, and user-friendly solution that empowers consumers and businesses to combat the adverse effects of counterfeit products, enhancing trust and safety in the marketplace.

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Cite This Article

ISSN: 2349-6002
Volume: 12
Issue: 1
PageNo: 1670-1673

Fake Products Detection Using Machine Learning

Available:https://ijirt.org/article?manuscript=180477

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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