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Sensors (Basel, Switzerland)
Feb 16, 2022
Machine Learning (ML) methods have become state of the art in radar signal processing, particularly for classification tasks (e.g., of different human activities). Radar classification can be tedious to implement, though, due to the limited size and ...
Sensors (Basel, Switzerland)
Feb 14, 2022
Mobile and wearable devices have enabled numerous applications, including activity tracking, wellness monitoring, and human-computer interaction, that measure and improve our daily lives. Many of these applications are made possible by leveraging the...
Sensors (Basel, Switzerland)
Feb 14, 2022
Group activity recognition is a prime research topic in video understanding and has many practical applications, such as crowd behavior monitoring, video surveillance, etc. To understand the multi-person/group action, the model should not only identi...
Sensors (Basel, Switzerland)
Feb 11, 2022
Human activity recognition (HAR) using wearable sensors is an increasingly active research topic in machine learning, aided in part by the ready availability of detailed motion capture data from smartphones, fitness trackers, and smartwatches. The go...
Journal of healthcare engineering
Feb 4, 2022
According to statistics, stroke is the second or third leading cause of death and adult disability. Stroke causes losing control of the motor function, paralysis of body parts, and severe back pain for which a physiotherapist employs many therapies t...
Sensors (Basel, Switzerland)
Jan 28, 2022
Human Activity Recognition (HAR) systems are designed to read sensor data and analyse it to classify any detected movement and respond accordingly. However, there is a need for more responsive and near real-time systems to distinguish between false a...
Sensors (Basel, Switzerland)
Jan 14, 2022
Due to the wide application of human activity recognition (HAR) in sports and health, a large number of HAR models based on deep learning have been proposed. However, many existing models ignore the effective extraction of spatial and temporal featur...
IEEE transactions on cybernetics
Jan 11, 2022
Data representation learning is one of the most important problems in machine learning. Unsupervised representation learning becomes meritorious as it has no necessity of label information with observed data. Due to the highly time-consuming learning...
Computational intelligence and neuroscience
Jan 10, 2022
The traditional human action recognition (HAR) method is based on RGB video. Recently, with the introduction of Microsoft Kinect and other consumer class depth cameras, HAR based on RGB-D (RGB-Depth) has drawn increasing attention from scholars and i...
PloS one
Jan 7, 2022
Multiple cameras are used to resolve occlusion problem that often occur in single-view human activity recognition. Based on the success of learning representation with deep neural networks (DNNs), recent works have proposed DNNs models to estimate hu...