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@article{176515,
        author = {Pradip Borade and Mangesh Bodke and Prateek Chakranarayan and Laxmi Borse and Smita Mulhar},
        title = {Intelligent Stroke Detection Using Convolutional Neural Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {5428-5432},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176515},
        abstract = {Cricket is one of the most viewed and played sports in the world. In Indian subcontinent cricket is viewed as a religion. In recent times there have been so much advancement in the technology related to sports field and cricket is not exception to that, from better cameras to edge detection accuracy is developing so fast. In this paper we have proposed method based on the Convolutional Neural Network to get better accuracy. Cricket, one of the most popular sports worldwide, especially in the Indian subcontinent, is not just a game but a passion followed by millions. The advent of advanced technologies in sports has transformed how the game is analysed, viewed, and understood. With the increasing availability of high-resolution cameras and sophisticated data analytics, there is a growing demand for automated systems that can provide in-depth insights into various aspects of the game. Among these, cricket shot detection has become an essential component in sports analytics, enabling coaches, analysts, and broadcasters to assess player performance more effectively.},
        keywords = {Cricket shots, Convolutional Neural Networks (CNN), Sports analytics, Deep learning Video analysis, Machine learning, and Image classification.},
        month = {April},
        }