NDLI: Convolutional neural networks for gender prediction from smartphone-based ocular images

Content Provider	IET Digital Library
Author	Rattani, Ajita Reddy, Narsi Derakhshani, Reza
Abstract	Automated gender prediction has drawn significant interest in numerous applications such as surveillance, human–computer interaction, anonymous customised advertisement system, image retrieval system, and biometrics. In the context of smartphone devices, gender information has been used to enhance the accuracy of the integrated biometric authentication and mobile healthcare system. Here, the authors thoroughly investigate gender prediction from ocular images acquired using front-facing cameras of smartphones. This is a new problem as previous research in this area has not explored RGB ocular images captured by smartphones. The authors used deep learning for the task. Specifically, pre-trained and custom convolutional neural network architectures have been implemented for gender prediction. Multi-classifier fusion has been used to improve the prediction accuracy. Further, evaluation of off-the-self-texture descriptors and study of human ability in gender prediction has been conducted for comparative analysis.
Starting Page	423
Ending Page	430
Page Count	8
ISSN	20474938
Volume Number	7
e-ISSN	20474946
Issue Number	Issue 5, Sep (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/7/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2017.0171
Journal	IET Biometrics
Publisher Date	2018-01-22
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Anonymous Customised Advertisement System Automated Gender Prediction Biology And Medical Computing Biomimetics Computer Vision And Image Processing Technique Convolution Convolutional Neural Network Architectures Feature Extraction Feedforward Neural Network Gender Information Gender Issues Healthcare Human Computer Interaction Human-computer Interaction Image Classification Image Colour Analysis Image Recognition Image Retrieval Image Retrieval System Information Retrieval Technique Integrated Biometric Authentication Knowledge Engineering Technique Learning in AI Mobile Healthcare System Neural Computing Technique Neural Net Architecture Pervasive Computing Pre-trained Network Architectures Smart Phones Smartphone Device Smartphone-based Ocular Image Ubiquitous User InterFace
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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