Deepiris: Iris recognition using a deep learning approach
S Minaee, A Abdolrashidi - arXiv preprint arXiv:1907.09380, 2019 - arxiv.org
Iris recognition has been an active research area during last few decades, because of its
wide applications in security, from airports to homeland security border control. Different …
wide applications in security, from airports to homeland security border control. Different …
Iris recognition with off-the-shelf CNN features: A deep learning perspective
Iris recognition refers to the automated process of recognizing individuals based on their iris
patterns. The seemingly stochastic nature of the iris stroma makes it a distinctive cue for …
patterns. The seemingly stochastic nature of the iris stroma makes it a distinctive cue for …
Towards more accurate iris recognition using deeply learned spatially corresponding features
Z Zhao, A Kumar - … of the IEEE international conference on …, 2017 - openaccess.thecvf.com
This paper proposes an accurate and generalizable deep learning framework for iris
recognition. The proposed framework is based on a fully convolutional network (FCN), which …
recognition. The proposed framework is based on a fully convolutional network (FCN), which …
Toward more accurate iris recognition using dilated residual features
Iris recognition has emerged as the more accurate, convenient, and low-cost biometric
approach to authenticate human subjects. However, the accuracy offered by current popular …
approach to authenticate human subjects. However, the accuracy offered by current popular …
An efficient and accurate iris recognition algorithm based on a novel condensed 2-ch deep convolutional neural network
Recently, deep learning approaches, especially convolutional neural networks (CNNs),
have attracted extensive attention in iris recognition. Though CNN-based approaches …
have attracted extensive attention in iris recognition. Though CNN-based approaches …
Deep learning-based feature extraction in iris recognition: Use existing models, fine-tune or train from scratch?
Modern deep learning techniques can be employed to generate effective feature extractors
for the task of iris recognition. The question arises: should we train such structures from …
for the task of iris recognition. The question arises: should we train such structures from …
Deep learning for iris recognition: A survey
In this survey, we provide a comprehensive review of more than 200 articles, technical
reports, and GitHub repositories published over the last 10 years on the recent …
reports, and GitHub repositories published over the last 10 years on the recent …
DeepIrisNet: Deep iris representation with applications in iris recognition and cross-sensor iris recognition
Despite significant advances in iris recognition (IR), the efficient and robust IR at scale and
in non-ideal conditions presents serious performance issues and is still ongoing research …
in non-ideal conditions presents serious performance issues and is still ongoing research …
Thirdeye: Triplet based iris recognition without normalization
Most iris recognition pipelines involve three stages: segmenting into iris/non-iris pixels,
normalization the iris region to a fixed area, and extracting relevant features for comparison …
normalization the iris region to a fixed area, and extracting relevant features for comparison …
An experimental study of deep convolutional features for iris recognition
S Minaee, A Abdolrashidiy… - 2016 IEEE signal …, 2016 - ieeexplore.ieee.org
Iris is one of the popular biometrics that is widely used for identity authentication. Different
features have been used to perform iris recognition in the past. Most of them are based on …
features have been used to perform iris recognition in the past. Most of them are based on …