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CBR Based Educational Method for the Postgraduate Course Image Processing and Machine Vision

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Book cover Intelligent Computing Methodologies (ICIC 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10956))

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Abstract

This paper discusses the urgency and importance of teaching innovation in the postgraduate course image processing and machine vision. Aiming to address the problem of deepen teaching innovation, this paper proposes a CBR based method to construct educational system. Besides, discussion on how to cultivate postgraduates’ scientific literacy and application ability is also conducted to further improve the teaching quality and effect of the image processing and machine vision postgraduate courses.

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Acknowledgement

This work is supported by the Educational Research Project from the Educational Commission of Hubei Province (2016234).

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Authors and Affiliations

  1. School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, China

    Xin Xu & Lei Liu

  2. Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System, Wuhan University of Science and Technology, Wuhan, China

    Xin Xu

Authors
  1. Xin Xu
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  2. Lei Liu
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Corresponding author

Correspondence to Xin Xu .

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Editors and Affiliations

  1. Tongji University, Shanghai, China

    De-Shuang Huang

  2. Indian Institute of Technology Madras, Chennai, India

    M. Michael Gromiha

  3. Inha University, Incheon, Korea (Republic of)

    Kyungsook Han

  4. Liverpool John Moores University, Liverpool, United Kingdom

    Abir Hussain

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Xu, X., Liu, L. (2018). CBR Based Educational Method for the Postgraduate Course Image Processing and Machine Vision. In: Huang, DS., Gromiha, M., Han, K., Hussain, A. (eds) Intelligent Computing Methodologies. ICIC 2018. Lecture Notes in Computer Science(), vol 10956. Springer, Cham. https://doi.org/10.1007/978-3-319-95957-3_55

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  • DOI: https://doi.org/10.1007/978-3-319-95957-3_55

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95956-6

  • Online ISBN: 978-3-319-95957-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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