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SCIENCE CHINA Information Sciences, Volume 62, Issue 1: 019104(2019) https://doi.org/10.1007/s11432-018-9512-1

Learning discriminative and invariant representation for fingerprint retrieval

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  • ReceivedApr 27, 2018
  • AcceptedMay 30, 2018
  • PublishedDec 19, 2018

Abstract

There is no abstract available for this article.


Acknowledgment

This work was supported by National Natural Science Foundation of China (Grant No. 61333015).


Supplement

Appendixes A–D.


References

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  • Figure 1

    (Color online) The distribution of learned deep convolutional features $\boldsymbol~f_c$ (without normalization) in fingerprint training data. A two-dimensional feature $\boldsymbol~f_c$ is learned by the DCNN with ten fingerprint classes. (a) Activation functions; (b) the distribution of features with rectified linear unit (ReLU); (c) the distribution of features with power function.

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