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@article{179474,
        author = {Masud Chowdhuri and Taniya Bandhu and Lisa Pramanick and Swastika Jash and Asman Ali SK},
        title = {A Framework for Predicting Image Recognition with the MTLSA Teachable Machine.},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {8173-8174},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179474},
        abstract = {Image identification is a key component of today's artificial intelligence applications, which significantly affect sectors including healthcare, retail, and security. This project uses Google's ARSAK Teachable Machine to create a predictive model for image recognition. The article describes the core concepts of the Teachable Machine, provides guidance on creating a photo recognition model, and assesses the model's performance in prediction tasks. We show experimental results based on a generated dataset and evaluate the model's accuracy, practicality, and potential for use in real-world scenarios.},
        keywords = {AI applications, machine learning, prediction models, teachable machines, and image recognition},
        month = {May},
        }