### Abstract

Deep learning for biometrics has increasingly gained attention over the last years.

The expansion of computational power and the increasing dataset sizes, increased

verification performances. However, large datasets are not available for every ap-

plication. We introduce Deep Verification Learning, to reduce network complex-

ity and train on smaller datasets. Deep Verification Learning takes two images

to be verified at the input of a network, and trains directly towards a verification

score. We applied Deep Verification Learning on the face verification task, also

it could be extended to other biometric modalities.

The expansion of computational power and the increasing dataset sizes, increased

verification performances. However, large datasets are not available for every ap-

plication. We introduce Deep Verification Learning, to reduce network complex-

ity and train on smaller datasets. Deep Verification Learning takes two images

to be verified at the input of a network, and trains directly towards a verification

score. We applied Deep Verification Learning on the face verification task, also

it could be extended to other biometric modalities.

Original language | English |
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Title of host publication | Proceedings of the 2017 Symposium on Information Theory and Signal Processing in the Benelux |

Subtitle of host publication | May 11-12, 2017, Delft University of Technology, Delft, the Netherlands |

Editors | Richard Heusden, Jos H. Weber |

Place of Publication | Delft |

Publisher | Delft University of Technology |

Pages | 97-104 |

ISBN (Print) | 978-94-6186-811-4 |

Publication status | Published - 2017 |

Event | 38th WIC Symposium on Information Theory in the Benelux 2017 - Delft, Netherlands Duration: 11 May 2017 → 12 May 2017 Conference number: 38 |

### Conference

Conference | 38th WIC Symposium on Information Theory in the Benelux 2017 |
---|---|

Country | Netherlands |

City | Delft |

Period | 11/05/17 → 12/05/17 |

### Keywords

- SCS-Safety
- FISWG
- Eyebrows
- Human verification performance

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## Cite this

Hillerström, F., Veldhuis, R., & Spreeuwers, L. (2017). Deep Verification Learning. In R. Heusden, & J. H. Weber (Eds.),

*Proceedings of the 2017 Symposium on Information Theory and Signal Processing in the Benelux: May 11-12, 2017, Delft University of Technology, Delft, the Netherlands*(pp. 97-104). Delft: Delft University of Technology.