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@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},
        }