Convolutional neural networks for gender prediction from smartphone‐based ocular images-Reference-Cited by-同舟云学术

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Convolutional neural networks for gender prediction from smartphone‐based ocular images

Published:2018-02-19 Issue:5 Volume:7 Page:423-430
ISSN:2047-4938
Container-title:IET Biometrics
language:en
Short-container-title:IET biom.

Author:

Rattani Ajita¹,Reddy Narsi¹,Derakhshani Reza¹

Affiliation:

1. Department of Computer Science and Electrical EngineeringUniversity of Missouri‐Kansas CityMOUSA

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-bmt.2017.0171

Reference39 articles.

1. Cao D. Chen C. Piccirilli M. et al. : ‘Can facial metrology predict gender?’.Int. Joint Conf. on Biometrics October2011 pp.1–8

2. Learning gender with support faces

3. Rattani A. Reddy N. Derakhshani R.: ‘Gender prediction from mobile ocular images: a feasibility study’.IEEE Symp. on Technologies for Homeland Security Waltham MA 2017 pp.1–6

4. Bobeldyk D. Ross A.: ‘Iris or periocular? Exploring sex prediction from near infrared ocular images’.Int. Conf. of the Biometrics Special Interest Group September2016 pp.1–7

5. Evaluation of gender classification methods with automatically detected and aligned faces;Makinen E.;IEEE Trans. Pattern Anal. Mach. Intell.,2008

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4. Artificial intelligence-assisted smartphone-based sensing for bioanalytical applications: A review;Biosensors and Bioelectronics;2023-06

5. Unconstrained Gender Recognition from Periocular Region Using Multiscale Deep Features;Intelligent Automation & Soft Computing;2023

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