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Olympic Sports Events Classification Using Convolutional Neural Networks

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Proceedings of International Joint Conference on Computational Intelligence

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

The analysis of different sports data to get valuable insight has become immensely important nowadays. Profuse application of Artificial Intelligence in different sectors has become a very popular trend as well. However, the application of AI in sports analytics is still a new research domain left for exploration. With a view to applying AI in sports analytics, we have deployed Inception V3 and MobileNet which are Google’s most popular Convolutional Neural Networks to successfully recognize five different sports events from a huge image dataset of these events. Both of the models have achieved a very high performance in terms of accuracy, precision, recall, and f-measure while applied to the target dataset for successful classification.

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Author information

Authors and Affiliations

  1. Department of CSE, Daffodil International University, Dhaka, Bangladesh

    Shahana Shultana, Md. Shakil Moharram & Nafis Neehal

Authors
  1. Shahana Shultana
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  2. Md. Shakil Moharram
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  3. Nafis Neehal
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Corresponding author

Correspondence to Shahana Shultana .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Jahangirnagar University, Dhaka, Bangladesh

    Mohammad Shorif Uddin

  2. Department of Mathematics, South Asian University, New Delhi, Delhi, India

    Jagdish Chand Bansal

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Shultana, S., Moharram, M.S., Neehal, N. (2020). Olympic Sports Events Classification Using Convolutional Neural Networks. In: Uddin, M., Bansal, J. (eds) Proceedings of International Joint Conference on Computational Intelligence. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-13-7564-4_43

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