Image segmentation using deep learning: A survey
Image segmentation is a key task in computer vision and image processing with important
applications such as scene understanding, medical image analysis, robotic perception …
applications such as scene understanding, medical image analysis, robotic perception …
Understanding deep learning techniques for image segmentation
The machine learning community has been overwhelmed by a plethora of deep learning--
based approaches. Many challenging computer vision tasks, such as detection, localization …
based approaches. Many challenging computer vision tasks, such as detection, localization …
Accurate iris segmentation and recognition using an end-to-end unified framework based on MADNet and DSANet
Y Chen, H Gan, H Chen, Y Zeng, L Xu, AA Heidari… - Neurocomputing, 2023 - Elsevier
Due to their insufficient generalization ability, iris segmentation algorithms based on deep
learning cannot accurately segment iris images without corresponding ground truth (GT) …
learning cannot accurately segment iris images without corresponding ground truth (GT) …
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 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 …
[HTML][HTML] A survey of identity recognition via data fusion and feature learning
With the rapid development of the Mobile Internet and the Industrial Internet of Things, a
variety of applications put forward an urgent demand for user and device identity …
variety of applications put forward an urgent demand for user and device identity …
Polymax: General dense prediction with mask transformer
Dense prediction tasks, such as semantic segmentation, depth estimation, and surface
normal prediction, can be easily formulated as per-pixel classification (discrete outputs) or …
normal prediction, can be easily formulated as per-pixel classification (discrete outputs) or …
Deep neural architectures for medical image semantic segmentation
MZ Khan, MK Gajendran, Y Lee, MA Khan - IEEE Access, 2021 - ieeexplore.ieee.org
Deep learning has an enormous impact on medical image analysis. Many computer-aided
diagnostic systems equipped with deep networks are rapidly reducing human intervention in …
diagnostic systems equipped with deep networks are rapidly reducing human intervention in …
Attention guided U-Net for accurate iris segmentation
Iris segmentation is a critical step for improving the accuracy of iris recognition, as well as for
medical concerns. Existing methods generally use whole eye images as input for network …
medical concerns. Existing methods generally use whole eye images as input for network …
A deep learning iris recognition method based on capsule network architecture
T Zhao, Y Liu, G Huo, X Zhu - IEEE Access, 2019 - ieeexplore.ieee.org
Iris recognition is one of the most representative identification technologies in biometric
recognition, which is widely used in various fields. Recently, many deep learning methods …
recognition, which is widely used in various fields. Recently, many deep learning methods …