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Image Classification Based on Deep Belief Network and YELM

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Intelligent Computing Theories and Application (ICIC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12463))

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Abstract

For a large amount of image data, an image classification method based on improved deep belief network (IDBN) and improved extreme learning machine (YELM) was proposed. Firstly, IDBN was used to simplify the complex high-dimensional data to lower dimensions space, and get the main inherent feature of the images with lower dimension. Then YELM was used to classify data after the dimension reduction. The proposed IDBN-YELM method has a significant improvement in classification accuracy. Extensive experiments were performed using challenging dataset and results were compared against the models such as DBN, YELM, IDBN-ELM. Though a lot of comparative experiments on the street view house numbers (SVHN) dataset, the results show that the IDBN-YELM has the high classification accuracy for the problem of large-scale image classification.

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Author information

Authors and Affiliations

  1. Jiangsu Vocational College of Information Technology, Wuxi, 214153, China

    ChengYong Zhang

  2. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou, 221116, China

    Zhengwei Li, Ru Nie & Huan Zhao

  3. Engineering Research Center of Mine Digitalization of Ministry of Education, China University of Mining and Technology, Xuzhou, 221116, China

    Zhengwei Li, Ru Nie & Huan Zhao

  4. Institute of Machine Learning and Systems Biology, College of Electronics and Information Engineering, Tongji University, Shanghai, 201804, China

    Zhengwei Li

  5. KUNPAND Communications (Kunshan) Co., Ltd, Suzhou, 215300, China

    Zhengwei Li

  6. School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou, 221116, China

    Lei Wang

Authors
  1. ChengYong Zhang
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  2. Zhengwei Li
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  3. Ru Nie
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  4. Lei Wang
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  5. Huan Zhao
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Corresponding authors

Correspondence to Zhengwei Li or Ru Nie .

Editor information

Editors and Affiliations

  1. Institute of Machine Learning and Systems Biology, Tongji University, Shanghai, China

    De-Shuang Huang

  2. Electrical and Electronics Department, Polytechnic University of Bari, Bari, Italy

    Vitoantonio Bevilacqua

  3. School of Computer Science and Mathematics, Liverpool John Moores University, Liverpool, UK

    Abir Hussain

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Zhang, C., Li, Z., Nie, R., Wang, L., Zhao, H. (2020). Image Classification Based on Deep Belief Network and YELM. In: Huang, DS., Bevilacqua, V., Hussain, A. (eds) Intelligent Computing Theories and Application. ICIC 2020. Lecture Notes in Computer Science(), vol 12463. Springer, Cham. https://doi.org/10.1007/978-3-030-60799-9_13

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  • DOI: https://doi.org/10.1007/978-3-030-60799-9_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-60798-2

  • Online ISBN: 978-3-030-60799-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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