Fake Products Detection Using Machine Learning

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

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{180477,
        author = {Prof. Shah Saloni Niranjan and Mrs.Kokare.S.A. and Rokade Dnyaneshwari and Avate Rutuja and Taware Sakshi},
        title = {Fake Products Detection Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {1670-1673},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180477},
        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.},
        keywords = {Counterfeit items and logos, of image recognition, pattern analysis, and AI-driven algorithms.},
        month = {June},
        }

Cite This Article

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

Fake Products Detection Using Machine Learning

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