InceptB: A CNN Based Classification Approach for Recognizing Traditional Bengali Games

InceptB: A CNN Based Classification Approach for Recognizing Traditional Bengali Games

Sports activities are an integral part of our day to day life. Introducing autonomous decision making and predictive models to recognize and analyze different sports events and activities has become an emerging trend in computer vision arena. Albeit the advances and vivid applications of artificial...

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Hauptverfasser: Islam, Mohammad Shakirul, Foysal, Ferdouse Ahmed, Neehal, Nafis, Karim, Enamul, Hossain, Syed Akhter
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Computer Science - Computer Vision and Pattern Recognition
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creator Islam, Mohammad Shakirul
Foysal, Ferdouse Ahmed
Neehal, Nafis
Karim, Enamul
Hossain, Syed Akhter
description Sports activities are an integral part of our day to day life. Introducing autonomous decision making and predictive models to recognize and analyze different sports events and activities has become an emerging trend in computer vision arena. Albeit the advances and vivid applications of artificial intelligence and computer vision in recognizing different popular western games, there remains a very minimal amount of efforts in the application of computer vision in recognizing traditional Bangladeshi games. We, in this paper, have described a novel Deep Learning based approach for recognizing traditional Bengali games. We have retrained the final layer of the renowned Inception V3 architecture developed by Google for our classification approach. Our approach shows promising results with an average accuracy of 80% approximately in correctly recognizing among 5 traditional Bangladeshi sports events.
doi_str_mv 10.48550/arxiv.1805.01442
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title InceptB: A CNN Based Classification Approach for Recognizing Traditional Bengali Games
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