Gait recognition is an appealing biometric modality which aims to identify individuals based
on the way they walk. Deep learning has reshaped the research landscape in this area …

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 …

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 …

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 …

Automatic person identification from ear images is an active field of research within the
biometric community. Similar to other biometrics such as face, iris and fingerprints, ear also …

Identity recognition using local features extracted from ear images has recently attracted a
great deal of attention in the intelligent biometric systems community. The rich and reliable …

A face-swap deep fake replaces a person's face--from eyebrows to chin--with another face.
A lip-sync deep fake replaces a person's mouth region to be consistent with an …

The recognition performance of visual recognition systems is highly dependent on extracting
and representing the discriminative characteristics of image data. Convolutional neural …

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 …

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 …