Deep CNN-LSTM with self-attention model for human activity recognition using wearable sensor
Human Activity Recognition (HAR) systems are devised for continuously observing human
behavior-primarily in the fields of environmental compatibility, sports injury detection, senior …
behavior-primarily in the fields of environmental compatibility, sports injury detection, senior …
A new deep-learning method for human activity recognition
Currently, three-dimensional convolutional neural networks (3DCNNs) are a popular
approach in the field of human activity recognition. However, due to the variety of methods …
approach in the field of human activity recognition. However, due to the variety of methods …
Wearable sensor-based human activity recognition with hybrid deep learning model
It is undeniable that mobile devices have become an inseparable part of human's daily
routines due to the persistent growth of high-quality sensor devices, powerful computational …
routines due to the persistent growth of high-quality sensor devices, powerful computational …
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 …
LSTM-CNN architecture for human activity recognition
K Xia, J Huang, H Wang - IEEE Access, 2020 - ieeexplore.ieee.org
In the past years, traditional pattern recognition methods have made great progress.
However, these methods rely heavily on manual feature extraction, which may hinder the …
However, these methods rely heavily on manual feature extraction, which may hinder the …
Hybrid deep learning approaches for smartphone sensor-based human activity recognition
V Ghate - Multimedia Tools and Applications, 2021 - Springer
Abstract Human Activity Recognition (HAR) has become one of the most important research
fields to achieve real-time monitoring of human activities for timely decision making in …
fields to achieve real-time monitoring of human activities for timely decision making in …
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 …
EnsemConvNet: a deep learning approach for human activity recognition using smartphone sensors for healthcare applications
Abstract Human Activity Recognition (HAR) can be defined as the automatic prediction of the
regular human activities performed in our day-to-day life, such as walking, running, cooking …
regular human activities performed in our day-to-day life, such as walking, running, cooking …
Human activity recognition via hybrid deep learning based model
In recent years, Human Activity Recognition (HAR) has become one of the most important
research topics in the domains of health and human-machine interaction. Many Artificial …
research topics in the domains of health and human-machine interaction. Many Artificial …
A CNN-LSTM approach to human activity recognition
R Mutegeki, DS Han - 2020 international conference on artificial …, 2020 - ieeexplore.ieee.org
To understand human behavior and intrinsically anticipate human intentions, research into
human activity recognition HAR) using sensors in wearable and handheld devices has …
human activity recognition HAR) using sensors in wearable and handheld devices has …