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International Conference on Recent Trends in Image Processing and Pattern Recognition

RTIP2R 2018: Recent Trends in Image Processing and Pattern Recognition pp 111–120Cite as

Shot-Net: A Convolutional Neural Network for Classifying Different Cricket Shots

Part of the Communications in Computer and Information Science book series (CCIS,volume 1035)

Abstract

Artificial Intelligence has become the new powerhouse of data analytics in this technological era. With advent of different Machine Learning and Computer Vision algorithms, applying them in data analytics has become a common trend. However, applying Deep Neural Networks in different sport data analyzing tasks and study the performance of these models is yet to be explored. Hence, in this paper, we have proposed a 13 layered Convolutional Neural Network referred as “Shot-Net” in order to classifying six categories of cricket shots, namely Cut Shot, Cover Drive, Straight Drive, Pull Shot, Scoop Shot and Leg Glance Shot. Our proposed model has achieved fairly high accuracy with low cross-entropy rate.

Keywords

  • Cricket shot classification
  • Convolution neural network
  • Deep learning

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Author information

Authors and Affiliations

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

    Md. Ferdouse Ahmed Foysal, Mohammad Shakirul Islam & Nafis Neehal

  2. College of Engineering and IT, Charles Darwin University, Darwin, Australia

    Asif Karim

Authors
  1. Md. Ferdouse Ahmed Foysal
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  2. Mohammad Shakirul Islam
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  3. Asif Karim
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  4. Nafis Neehal
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Corresponding author

Correspondence to Md. Ferdouse Ahmed Foysal .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Solapur University, Solapur, India

    Ravindra S. Hegadi

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Cite this paper

Foysal, M.F.A., Islam, M.S., Karim, A., Neehal, N. (2019). Shot-Net: A Convolutional Neural Network for Classifying Different Cricket Shots. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1035. Springer, Singapore. https://doi.org/10.1007/978-981-13-9181-1_10

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  • DOI: https://doi.org/10.1007/978-981-13-9181-1_10

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9180-4

  • Online ISBN: 978-981-13-9181-1

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