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@article{179041,
        author = {M. Jai Durga Bhavani and P. Sneha and A. Mahitha and M. Akshitha},
        title = {Fake Product Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {6437-6443},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179041},
        abstract = {In recent years, There are many more counterfeit products. It became easier in the production of  fake products. The main purpose is to check whether the items are real or fake. The aim is to check the product images, price, product description and barcodes if they match, can be conclude it as original items. This helps the people for not buying such counterfeit products and by reducing such things the people can trust and can buy anything. Not only the general products this play a major role in medical, it is very dangerous. This paper will provide a better solution for counterfeit products using Artificial Intelligence. These fake products are mainly in the online shopping system. This project has the potential to greatly reduce the impact of counterfeit goods on online platforms. It offers a scalable, automated solution that can work across different product categories and languages. To test this System, we collect the data from the different online platforms and declare it as real or fake. This gives the trust to people who shop on online and doesn’t encourage the fake products.},
        keywords = {Artificial Intelligence, Counterfeit, Medical, Barcodes, Real and fake products.},
        month = {May},
        }