Iris recognition development techniques: a comprehensive review

JR Malgheet, NB Manshor, LS Affendey - Complexity, 2021 - Wiley Online Library
Recently, iris recognition techniques have achieved great performance in identification.
Among authentication techniques, iris recognition systems have received attention very …

Deep learning for iris recognition: a review

Y Yin, S He, R Zhang, H Chang, X Han… - arXiv preprint arXiv …, 2023 - arxiv.org
Iris recognition is a secure biometric technology known for its stability and privacy. With no
two irises being identical and little change throughout a person's lifetime, iris recognition is …

FRED-Net: Fully residual encoder–decoder network for accurate iris segmentation

M Arsalan, DS Kim, MB Lee, M Owais… - Expert Systems with …, 2019 - Elsevier
Iris recognition is now developed enough to recognize a person from a distance. The
process of iris segmentation plays a vital role in maintaining the accuracy of the iris-based …

Attention-based DenseNet for pneumonia classification

K Wang, P Jiang, J Meng, X Jiang - Irbm, 2022 - Elsevier
Objective The structural complexity and uneven gray distribution of pneumonia images
seriously affect the accuracy of pneumonia classification. As DenseNet has the characteristic …

Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets

V Varkarakis, S Bazrafkan, P Corcoran - Neural Networks, 2020 - Elsevier
A data augmentation methodology is presented and applied to generate a large dataset of
off-axis iris regions and train a low-complexity deep neural network. Although of low …

PixISegNet: pixel‐level iris segmentation network using convolutional encoder–decoder with stacked hourglass bottleneck

RR Jha, G Jaswal, D Gupta, S Saini, A Nigam - IET biometrics, 2020 - Wiley Online Library
In this paper, we present a new iris ROI segmentation algorithm using a deep convolutional
neural network (NN) to achieve the state‐of‐the‐art segmentation performance on well …

Unravelling small sample size problems in the deep learning world

R Keshari, S Ghosh, S Chhabra… - 2020 IEEE Sixth …, 2020 - ieeexplore.ieee.org
The growth and success of deep learning approaches can be attributed to two major factors:
availability of hardware resources and availability of large number of training samples. For …

Fully convolutional networks and generative adversarial networks applied to sclera segmentation

DR Lucio, R Laroca, E Severo… - 2018 IEEE 9th …, 2018 - ieeexplore.ieee.org
Due to the world's demand for security systems, biometrics can be seen as an important
topic of research in computer vision. One of the biometric forms that has been gaining …

Supervised contrastive learning and intra-dataset adversarial adaptation for iris segmentation

Z Zhou, Y Liu, X Zhu, S Liu, S Zhang, Y Li - Entropy, 2022 - mdpi.com
Precise iris segmentation is a very important part of accurate iris recognition. Traditional iris
segmentation methods require complex prior knowledge and pre-and post-processing and …

MTCD: Cataract detection via near infrared eye images

P Tripathi, Y Akhter, M Khurshid, A Lakra… - Computer Vision and …, 2022 - Elsevier
Globally, cataract is a common eye disease and one of the leading causes of blindness and
vision impairment. The traditional process of detecting cataracts involves eye examination …