AIMC Topic: Iris
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Light microscopic iris classification using ensemble multi-class support vector machine.
Microscopy research and technique
Jan 12, 2021
Similar to other biometric systems such as fingerprint, face, DNA, iris classification could assist law enforcement agencies in identifying humans. Iris classification technology helps law-enforcement agencies to recognize humans by matching their ir...
Angle-closure assessment in anterior segment OCT images via deep learning.
Medical image analysis
Jan 7, 2021
Precise characterization and analysis of anterior chamber angle (ACA) are of great importance in facilitating clinical examination and diagnosis of angle-closure disease. Currently, the gold standard for diagnostic angle assessment is observation of ...
Deep Learning for Anterior Segment Optical Coherence Tomography to Predict the Presence of Plateau Iris.
Translational vision science & technology
Jan 6, 2021
PURPOSE: The purpose of this study was to evaluate the diagnostic performance of deep learning (DL) anterior segment optical coherence tomography (AS-OCT) as a plateau iris prediction model.
Deep Learning Model for Accurate Automatic Determination of Phakic Status in Pediatric and Adult Ultrasound Biomicroscopy Images.
Translational vision science & technology
Dec 23, 2020
PURPOSE: Ultrasound biomicroscopy (UBM) is a noninvasive method for assessing anterior segment anatomy. Previous studies were prone to intergrader variability, lacked assessment of the lens-iris diaphragm, and excluded pediatric subjects. Lens status...
Deep Learning Approach for Multimodal Biometric Recognition System Based on Fusion of Iris, Face, and Finger Vein Traits.
Sensors (Basel, Switzerland)
Sep 27, 2020
With the increasing demand for information security and security regulations all over the world, biometric recognition technology has been widely used in our everyday life. In this regard, multimodal biometrics technology has gained interest and beca...
Person identification using fusion of iris and periocular deep features.
Neural networks : the official journal of the International Neural Network Society
Nov 23, 2019
A novel method for person identification based on the fusion of iris and periocular biometrics has been proposed in this paper. The challenges for image acquisition for Near-Infrared or Visual Wavelength lights under constrained and unconstrained env...
Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets.
Neural networks : the official journal of the International Neural Network Society
Aug 1, 2019
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 complexity the resulting network achieves a high level of accuracy in iris r...
Deep Learning-Based Enhanced Presentation Attack Detection for Iris Recognition by Combining Features from Local and Global Regions Based on NIR Camera Sensor.
Sensors (Basel, Switzerland)
Aug 8, 2018
Iris recognition systems have been used in high-security-level applications because of their high recognition rate and the distinctiveness of iris patterns. However, as reported by recent studies, an iris recognition system can be fooled by the use o...
An end to end Deep Neural Network for iris segmentation in unconstrained scenarios.
Neural networks : the official journal of the International Neural Network Society
Jun 30, 2018
With the increasing imaging and processing capabilities of today's mobile devices, user authentication using iris biometrics has become feasible. However, as the acquisition conditions become more unconstrained and as image quality is typically lower...
Machine learning techniques for medical diagnosis of diabetes using iris images.
Computer methods and programs in biomedicine
Jan 11, 2018
BACKGROUND AND OBJECTIVE: Complementary and alternative medicine techniques have shown their potential for the treatment and diagnosis of chronical diseases like diabetes, arthritis etc. On the same time digital image processing techniques for diseas...
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