Due to their insufficient generalization ability, iris segmentation algorithms based on deep
learning cannot accurately segment iris images without corresponding ground truth (GT) …

Recently, iris recognition techniques have achieved great performance in identification.
Among authentication techniques, iris recognition systems have received attention very …

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 …

The pupil recognition method is helpful in many real-time systems, including ophthalmology
testing devices, wheelchair assistance, and so on. The pupil detection system is a very …

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 …

Automatic segmentation of retinal images is an important task in computer-assisted medical
image analysis for the diagnosis of diseases such as hypertension, diabetic and …

CNN-based iris segmentations have been proven to be superior to traditional iris
segmentation techniques in terms of segmentation error metrics. To properly utilize them in a …

With rapid development of satellite and airplane platforms, aerial image has become more
and more accessible. Aerial image scene classification plays an important role in many …

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 …

Iris segmentation plays an important and significant role in the iris recognition system. The
prerequisite for accurate iris recognition is the correctness of iris segmentation. However, the …