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One-Shot Learning Using Triplet Network with kNN Classifier

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Advances in Artificial Intelligence (JSAI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1128))

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Abstract

This is an extension from a selected paper from JSAI2019. Humans have the ability to learn new things correctly without requiring large amount of data, while it is a challenging task in AI, which is called few-shot Learning or one-shot learning. Our key insight is using data augmentation technique to enlarge our dataset, then feeding them into a Triplet Network which is to collect same categories and separate the different. We have compared different augmentation methods, and we confirm that CVAE(Conditional VAE) can make sense as data augmentation method to slove one-shot classification problems.

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Acknowledgement

This paper is based on results obtained from a project commissioned by the New Energy and Industrial Technology Development Organization (NEDO). This work was supported by JSPS KAKENHI Grant Number JP16K00116.

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Authors and Affiliations

  1. University of Tsukuba, Tsukuba, Japan

    Mu Zhou, Yusuke Tanimura & Hidemoto Nakada

  2. Artifical Intelligence Research Center, National Institute of Advanced Industrial Science and Technology(AIST), Tsukuba, Japan

    Mu Zhou, Yusuke Tanimura & Hidemoto Nakada

Authors
  1. Mu Zhou
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  2. Yusuke Tanimura
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  3. Hidemoto Nakada
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Corresponding author

Correspondence to Mu Zhou .

Editor information

Editors and Affiliations

  1. Department of Systems Innovation, University of Tokyo, Tokyo, Japan

    Yukio Ohsawa

  2. Faculty of Business and Commerce, Kansai University, Osaka, Japan

    Katsutoshi Yada

  3. Nagoya Institute of Technology, Nagoya, Japan

    Takayuki Ito

  4. Graduate School of System Design, Tokyo Metropolitan University, Tokyo, Japan

    Yasufumi Takama

  5. Department of Information and Communication, Tokyo Metropolitan University, Tokyo, Japan

    Eri Sato-Shimokawara

  6. Faculty of Letters, Chiba University, Chiba, Japan

    Akinori Abe

  7. School of Engineering, The University of Tokyo, Tokyo, Japan

    Junichiro Mori

  8. Graduate School of Economics, Osaka University, Toyonaka, Osaka, Japan

    Naohiro Matsumura

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Zhou, M., Tanimura, Y., Nakada, H. (2020). One-Shot Learning Using Triplet Network with kNN Classifier. In: Ohsawa, Y., et al. Advances in Artificial Intelligence. JSAI 2019. Advances in Intelligent Systems and Computing, vol 1128. Springer, Cham. https://doi.org/10.1007/978-3-030-39878-1_21

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