Deep learning for biometrics: A survey
K Sundararajan, DL Woodard - ACM Computing Surveys (CSUR), 2018 - dl.acm.org
In the recent past, deep learning methods have demonstrated remarkable success for
supervised learning tasks in multiple domains including computer vision, natural language …
supervised learning tasks in multiple domains including computer vision, natural language …
A comprehensive review of deep-learning-based methods for image forensics
I Castillo Camacho, K Wang - Journal of imaging, 2021 - mdpi.com
Seeing is not believing anymore. Different techniques have brought to our fingertips the
ability to modify an image. As the difficulty of using such techniques decreases, lowering the …
ability to modify an image. As the difficulty of using such techniques decreases, lowering the …
Biometrics recognition using deep learning: A survey
In the past few years, deep learning-based models have been very successful in achieving
state-of-the-art results in many tasks in computer vision, speech recognition, and natural …
state-of-the-art results in many tasks in computer vision, speech recognition, and natural …
Towards complete and accurate iris segmentation using deep multi-task attention network for non-cooperative iris recognition
Iris images captured in non-cooperative environments often suffer from adverse noise, which
challenges many existing iris segmentation methods. To address this problem, this paper …
challenges many existing iris segmentation methods. To address this problem, this paper …
Deep feature fusion for iris and periocular biometrics on mobile devices
The quality of iris images on mobile devices is significantly degraded due to hardware
limitations and less constrained environments. Traditional iris recognition methods cannot …
limitations and less constrained environments. Traditional iris recognition methods cannot …
[HTML][HTML] An investigation of biometric authentication in the healthcare environment
J Mason, R Dave, P Chatterjee, I Graham-Allen… - Array, 2020 - Elsevier
A vast amount of growth has taken place in the field of biometrics and in the healthcare
industry. Biometrics provides the ability to identify individuals based on their physical and …
industry. Biometrics provides the ability to identify individuals based on their physical and …
An end to end deep neural network for iris segmentation in unconstrained scenarios
With the increasing imaging and processing capabilities of today's mobile devices, user
authentication using iris biometrics has become feasible. However, as the acquisition …
authentication using iris biometrics has become feasible. However, as the acquisition …
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 …
Deep learning-based iris segmentation for iris recognition in visible light environment
Existing iris recognition systems are heavily dependent on specific conditions, such as the
distance of image acquisition and the stop-and-stare environment, which require significant …
distance of image acquisition and the stop-and-stare environment, which require significant …
IrisDenseNet: Robust iris segmentation using densely connected fully convolutional networks in the images by visible light and near-infrared light camera sensors
The recent advancements in computer vision have opened new horizons for deploying
biometric recognition algorithms in mobile and handheld devices. Similarly, iris recognition …
biometric recognition algorithms in mobile and handheld devices. Similarly, iris recognition …