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@article{179468,
        author = {Aditi Rej and Rupsha Sekh and Sayan Hazra and Avijit Kaibartya and Kartick Das},
        title = {A Structure for Image Recognition Prediction Using the ARSAK Teachable Machine.},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {8171-8172},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179468},
        abstract = {Today's artificial intelligence applications depend heavily on image identification, which has a big impact on industries like healthcare, retail, and security. This project builds a predictive model for picture identification using Google's ARSAK Teachable Machine. The article outlines the fundamental ideas of the Teachable Machine, offers advice on building a model for picture recognition, and evaluates how well it performs in prediction challenges. We analyze the model's correctness, usefulness, and potential for use in real-world situations while presenting experimental results based on a produced dataset.},
        keywords = {AI applications, machine learning, prediction models, teachable machines, and image recognition},
        month = {May},
        }