This paper presents a comprehensive exposition of deep learning architectures and
pipelines for biometric applications using complex characteristics of human gait. The variety …

Gait recognition aims at identifying a person at a distance through visual cameras. With the
emergence of deep learning, significant advancements in gait recognition have achieved …

Gait recognition aims at identifying different people by the walking patterns, which can be
conducted at a long distance without the cooperation of subjects. A key challenge for gait …

Gait is one of the most promising biometrics that aims to identify pedestrians from their
walking patterns. However, prevailing methods are susceptible to confounders, resulting in …

Smart healthcare applications depend on data from wearable sensors (WSs) mounted on a
patient's body for frequent monitoring information. Healthcare systems depend on multi-level …

The accurate segmentation of medical images plays a crucial role in diagnosing and treating
diseases. Although many methods now use multimodal joint segmentation, the joint use of …

Indoor human activity recognition is actively studied as part of creating various intelligent
systems with applications in smart home and office, smart health, internet of things, etc …

Gait recognition is a biometric technology that identifies people by their walking patterns.
The silhouettes-based method and the skeletons-based method are the two most popular …

Gait recognition is an essential biometric technique that recognizes humans at a distance
through their unique walking style. In the present era of deep learning, automated gait …

In recent years, single modality-based gait recognition has been extensively explored in the
analysis of medical images or other sensory data, and it is recognized that each of the …