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@article{155212,
        author = {GAUTAMI DEOKAR and Avinashdev Garudapalli  and Shreya Jalgaonkar},
        title = {VIRTUAL PET ADOPTION AND BREED IDENTIFICATION},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {1},
        pages = {640-645},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=155212},
        abstract = {The Previous product provides the citizens to adopt from our website and also allows us to create a social account where people can interact with each other. The Product also allows us to identify the breed in the post using Machine Learning and Deep Learning. We are using this feature to avoid any fraudulent post. The product also has IoT enabled features such as tracking. Index. With the previous product in mind, we improved the product with more accurate model which has 2X speed to classify properly. This model not just improved accuracy but has very less chances of mis prediction. This model gives us 95% of accuracy which is proved to be good and very useful.},
        keywords = {Machine learning. Deep Learning, Python, Django, Firebase, MySql, IOT, Streamlit.},
        month = {},
        }