A survey of 3d ear recognition techniques
Human recognition with biometrics is a rapidly emerging area of computer vision. Compared
to other well-known biometric features such as the face, fingerprint, iris, and palmprint, the …
to other well-known biometric features such as the face, fingerprint, iris, and palmprint, the …
A comprehensive survey and deep learning-based approach for human recognition using ear biometric
Human recognition systems based on biometrics are much in demand due to increasing
concerns of security and privacy. The human ear is unique and useful for recognition. It …
concerns of security and privacy. The human ear is unique and useful for recognition. It …
Diabetic retinopathy diagnosis from fundus images using stacked generalization of deep models
Diabetic retinopathy (DR) is a diabetes complication that affects the eye and can cause
damage from mild vision problems to complete blindness. It has been observed that the eye …
damage from mild vision problems to complete blindness. It has been observed that the eye …
Ear recognition based on deep unsupervised active learning
Y Khaldi, A Benzaoui, A Ouahabi… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Cooperative machine learning has many applications, such as data annotation, where an
initial model trained with partially labeled data is used to predict labels for unseen data …
initial model trained with partially labeled data is used to predict labels for unseen data …
COVID-Nets: deep CNN architectures for detecting COVID-19 using chest CT scans
In this paper we propose two novel deep convolutional network architectures, CovidResNet
and CovidDenseNet, to diagnose COVID-19 based on CT images. The models enable …
and CovidDenseNet, to diagnose COVID-19 based on CT images. The models enable …
Deep convolutional neural networks for unconstrained ear recognition
This paper employs state-of-the-art Deep Convolutional Neural Networks (CNNs), namely
AlexNet, VGGNet, Inception, ResNet and ResNeXt in a first experimental study of ear …
AlexNet, VGGNet, Inception, ResNet and ResNeXt in a first experimental study of ear …
A comprehensive survey on ear recognition: databases, approaches, comparative analysis, and open challenges
Automatic identity recognition from ear images is an active research topic in the biometric
community. The ability to secretly acquire images of the ear remotely and the stability of the …
community. The ability to secretly acquire images of the ear remotely and the stability of the …
Towards explainable ear recognition systems using deep residual networks
This paper presents ear recognition models constructed with Deep Residual Networks
(ResNet) of various depths. Due to relatively limited amounts of ear images we propose …
(ResNet) of various depths. Due to relatively limited amounts of ear images we propose …
MDFNet: An unsupervised lightweight network for ear print recognition
In this paper, we propose an unsupervised lightweight network with a single layer for ear
print recognition. We refer to this method by MDFNet because it relies on gradient …
print recognition. We refer to this method by MDFNet because it relies on gradient …
Feature extraction with handcrafted methods and convolutional neural networks for facial emotion recognition
This research compares the facial expression recognition accuracy achieved using image
features extracted (a) manually through handcrafted methods and (b) automatically through …
features extracted (a) manually through handcrafted methods and (b) automatically through …