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Information Fusion Based on Metric Learning

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Information Fusion

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Abstract

Metric learning aims to measure the similarity or dissimilarity between each pair of samples. Until now, various types of metrics are studied and achieve satisfied performances in many applications. To comprehensively exploit the advantages of different metrics, this chapter proposes two metric fusion methods and applies them to classification and verification. After reading this chapter people can have preliminary knowledge on metric learning based fusion algorithms.

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Author information

Authors and Affiliations

  1. Harbin Institute of Technology, Shenzhen School of Computer Science and Technology Xili, Nanshan, Shenzhen, China

    Jinxing Li

  2. Department of Computer and Information Science, The University of Macau, Macau, China

    Bob Zhang

  3. School of Science and Engineering, The Chinese University of Hong Kong (Shenzhen), Shenzhen, China

    David Zhang

Authors
  1. Jinxing Li
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  2. Bob Zhang
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  3. David Zhang
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Li, J., Zhang, B., Zhang, D. (2022). Information Fusion Based on Metric Learning. In: Information Fusion. Springer, Singapore. https://doi.org/10.1007/978-981-16-8976-5_5

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  • DOI: https://doi.org/10.1007/978-981-16-8976-5_5

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-8975-8

  • Online ISBN: 978-981-16-8976-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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