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Analysis of Texture Representation in Convolution Neural Network Using Wavelet Based Joint Statistics

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Neural Information Processing (ICONIP 2020)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12532))

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Abstract

We analyze the texture representation ability in a deep convolution neural network called VGG. For analysis, we introduce a kind of wavelet-based joint statistics called minPS that applied to the visual neuron analysis. The minPS consists of 30 dimension features, which come from several types of statistics and correlations. We apply LASSO regression to the VGG representation in order to explain the minPS features. We find that the different scale type cross-correlation does not appear in the VGG representation from the regression weight analysis. Moreover, we synthesize the texture image from the VGG in the context of the style-transfer; we confirm the lack of different scale correlations influences the periodic texture to synthesize.

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Acknowledgment

We thank to the Mr. Satoshi Suzuki and Mr. Takahiro Kawashima for fruitful discussion about the mathematical modeling. This study was partly supported with MEXT KAKENHI, Grant-in-Aid for Scientific Research on Innovative Areas, 19H04982, Grant-in-Aid for Scientific Research (A) 18H04106.

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Authors and Affiliations

  1. The University of Electro-Communications, Chofu, Tokyo, Japan

    Yusuke Hamano & Hayaru Shouno

Authors
  1. Yusuke Hamano
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  2. Hayaru Shouno
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Corresponding author

Correspondence to Hayaru Shouno .

Editor information

Editors and Affiliations

  1. Department of AI, Ping An Life, Shenzhen, China

    Haiqin Yang

  2. Faculty of Information Technology, King Mongkut's Institute of Technology Ladkrabang, Bangkok, Thailand

    Kitsuchart Pasupa

  3. City University of Hong Kong, Kowloon, Hong Kong

    Andrew Chi-Sing Leung

  4. Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, Hong Kong

    James T. Kwok

  5. School of Information Technology, King Mongkut’s University of Technology Thonburi, Bangkok, Thailand

    Jonathan H. Chan

  6. The Chinese University of Hong Kong, New Territories, Hong Kong

    Irwin King

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Hamano, Y., Shouno, H. (2020). Analysis of Texture Representation in Convolution Neural Network Using Wavelet Based Joint Statistics. In: Yang, H., Pasupa, K., Leung, A.CS., Kwok, J.T., Chan, J.H., King, I. (eds) Neural Information Processing. ICONIP 2020. Lecture Notes in Computer Science(), vol 12532. Springer, Cham. https://doi.org/10.1007/978-3-030-63830-6_11

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  • DOI: https://doi.org/10.1007/978-3-030-63830-6_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-63829-0

  • Online ISBN: 978-3-030-63830-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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