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 …
Human activity recognition using wearable sensors by deep convolutional neural networks
W Jiang, Z Yin - Proceedings of the 23rd ACM international conference …, 2015 - dl.acm.org
Human physical activity recognition based on wearable sensors has applications relevant to
our daily life such as healthcare. How to achieve high recognition accuracy with low …
our daily life such as healthcare. How to achieve high recognition accuracy with low …
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 …
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 …
A human activity recognition method based on lightweight feature extraction combined with pruned and quantized CNN for wearable device
Human Activity Recognition (HAR) is becoming an essential part of human life care. Existing
HAR methods are usually developed using a two-level approach, wherein a first-level …
HAR methods are usually developed using a two-level approach, wherein a first-level …
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 …
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 robust human activity recognition system using smartphone sensors and deep learning
In last few decades, human activity recognition grabbed considerable research attentions
from a wide range of pattern recognition and human–computer interaction researchers due …
from a wide range of pattern recognition and human–computer interaction researchers due …
An adaptive batch size-based-CNN-LSTM framework for human activity recognition in uncontrolled environment
NA Choudhury, B Soni - IEEE Transactions on Industrial …, 2023 - ieeexplore.ieee.org
Human activity recognition (HAR) is a process of identifying the daily living activities of an
individual using a set of sensors and appropriate learning algorithms. Most of the works on …
individual using a set of sensors and appropriate learning algorithms. Most of the works on …