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Comparative Analysis of Restricted Boltzmann Machine Models for Image Classification

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Intelligent Information and Database Systems (ACIIDS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12034))

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Abstract

Many applications for Restricted Boltzmann Machines (RBM) have been developed for a large variety of learning problems. Recent developments have demonstrated the capacity of RBM to be powerful generative models, able to extract useful features from input data or construct deep artificial neural networks. In this work, we propose a learning algorithm to find the optimal model complexity for the RBM by improving the hidden layer. We compare the classification performance of regular RBM use RBM() function, classification RBM use stackRBM() function and Deep Belief Network (DBN) use DBN() function with different hidden layer. As a result, Stacking RBM and DBN could improve our classification performance compare to regular RBM.

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Acknowledgment

This paper is supported by Ministry of Science and Technology, Taiwan. The Nos are MOST-107-2221-E-324-018-MY2 and MOST-106-2218-E-324-002, Taiwan.

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Authors and Affiliations

  1. Department of Information Management, Chaoyang University of Technology, Taichung, Taiwan, R.O.C.

    Christine Dewi, Rung-Ching Chen & Hsiu-Te Hung

  2. Faculty of Information Technology, Satya Wacana Christian University, Salatiga, Indonesia

    Christine Dewi &  Hendry

Authors
  1. Christine Dewi
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  2. Rung-Ching Chen
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  3. Hendry
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  4. Hsiu-Te Hung
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Corresponding author

Correspondence to Rung-Ching Chen .

Editor information

Editors and Affiliations

  1. Department of Applied Informatics, Wrocław University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

  2. King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand

    Kietikul Jearanaitanakij

  3. Faculty of Computer Science and Information, University Teknologi Malaysia, Kuala Lumpur, Malaysia

    Ali Selamat

  4. Department of Applied Informatics, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

  5. King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand

    Suphamit Chittayasothorn

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Dewi, C., Chen, RC., Hendry, Hung, HT. (2020). Comparative Analysis of Restricted Boltzmann Machine Models for Image Classification. In: Nguyen, N., Jearanaitanakij, K., Selamat, A., Trawiński, B., Chittayasothorn, S. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Lecture Notes in Computer Science(), vol 12034. Springer, Cham. https://doi.org/10.1007/978-3-030-42058-1_24

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  • DOI: https://doi.org/10.1007/978-3-030-42058-1_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-42057-4

  • Online ISBN: 978-3-030-42058-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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