Human activity recognition from multiple sensors data using deep CNNs
Smart devices with sensors now enable continuous measurement of activities of daily living.
Accordingly, various human activity recognition (HAR) experiments have been carried out …
Accordingly, various human activity recognition (HAR) experiments have been carried out …
[HTML][HTML] Human activity recognition based on residual network and BiLSTM
Y Li, L Wang - Sensors, 2022 - mdpi.com
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 …
number of HAR models based on deep learning have been proposed. However, many …
Wearable Sensor‐Based Human Activity Recognition Using Hybrid Deep Learning Techniques
H Wang, J Zhao, J Li, L Tian, P Tu… - Security and …, 2020 - Wiley Online Library
Human activity recognition (HAR) can be exploited to great benefits in many applications,
including elder care, health care, rehabilitation, entertainment, and monitoring. Many …
including elder care, health care, rehabilitation, entertainment, and monitoring. Many …
Ultanet: An antithesis neural network for recognizing human activity using inertial sensors signals
HA Imran - IEEE Sensors Letters, 2022 - ieeexplore.ieee.org
Human activity recognition (HAR) is an essential component of ambient assistive living. HAR
has traditionally relied on computer vision techniques. However, it has several drawbacks …
has traditionally relied on computer vision techniques. However, it has several drawbacks …
A hybrid approach for human activity recognition with support vector machine and 1D convolutional neural network
The Human Activity Recognition (HAR) is a pattern recognition task that learns to identify
human physical activities recorded by different sensor modalities. The application areas …
human physical activities recorded by different sensor modalities. The application areas …
TSE-CNN: A two-stage end-to-end CNN for human activity recognition
J Huang, S Lin, N Wang, G Dai, Y Xie… - IEEE journal of …, 2019 - ieeexplore.ieee.org
Human activity recognition has been widely used in healthcare applications such as elderly
monitoring, exercise supervision, and rehabilitation monitoring. Compared with other …
monitoring, exercise supervision, and rehabilitation monitoring. Compared with other …
[HTML][HTML] A fast and robust deep convolutional neural networks for complex human activity recognition using smartphone
As a significant role in healthcare and sports applications, human activity recognition (HAR)
techniques are capable of monitoring humans' daily behavior. It has spurred the demand for …
techniques are capable of monitoring humans' daily behavior. It has spurred the demand for …
A novel attention-based convolution neural network for human activity recognition
G Zheng - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
Human Activity Recognition (HAR) has been widely used for various applications, such as
smart homes, healthcare, security and human-robot interaction. In this paper, a novel deep …
smart homes, healthcare, security and human-robot interaction. In this paper, a novel deep …
Aroma: A deep multi-task learning based simple and complex human activity recognition method using wearable sensors
L Peng, L Chen, Z Ye, Y Zhang - Proceedings of the ACM on Interactive …, 2018 - dl.acm.org
Human activity recognition (HAR) is a promising research issue in ubiquitous and wearable
computing. However, there are some problems existing in traditional methods: 1) They treat …
computing. However, there are some problems existing in traditional methods: 1) They treat …
Deep learning for sensor-based human activity recognition: Overview, challenges, and opportunities
The vast proliferation of sensor devices and Internet of Things enables the applications of
sensor-based activity recognition. However, there exist substantial challenges that could …
sensor-based activity recognition. However, there exist substantial challenges that could …