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A survey on periocular biometrics research

  • Published:2016-10 Issue: Volume:82 Page:92-105
  • ISSN:0167-8655
  • Container-title:Pattern Recognition Letters
  • language:en
  • Short-container-title:Pattern Recognition Letters

Author:

Alonso-Fernandez Fernando,Bigun Josef

Funder

Swedish Research Council

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference88 articles.

1. Genetic-based type ii feature extraction for periocular biometric recognition: less is more;Adams,2010

2. Periocular recognition using retinotopic sampling and gabor decomposition;Alonso-Fernandez,2012

3. Best regions for periocular recognition with NIR and visible images;Alonso-Fernandez,2014

4. Eye detection by complex filtering for periocular recognition;Alonso-Fernandez,2014

5. Near-infrared and visible-light periocular recognition with gabor features using frequency-adaptive automatic eye detection;Alonso-Fernandez;IET Biometrics,2015

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1. Periocular embedding learning with consistent knowledge distillation from face;Neurocomputing;2024-03

2. Boosting Multi-modal Ocular Recognition via Spatial Feature Reconstruction and Unsupervised Image Quality Estimation;Machine Intelligence Research;2024-01-15

3. An Explainable Model-Agnostic Algorithm for CNN-Based Biometrics Verification;2023 IEEE International Workshop on Information Forensics and Security (WIFS);2023-12-04

4. Eye Biometrics Combined with Periocular and Iris Recognition Using CNN;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31

5. Gender determination from periocular images using deep learning based EfficientNet architecture;International Journal of Mathematics and Computer in Engineering;2023-10-31
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