Deep learning in human activity recognition with wearable sensors: A review on advances
Mobile and wearable devices have enabled numerous applications, including activity
tracking, wellness monitoring, and human–computer interaction, that measure and improve …
tracking, wellness monitoring, and human–computer interaction, that measure and improve …
A survey on deep learning for human activity recognition
Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …
home. In this study, we provide a comprehensive survey on recent advances and challenges …
A multibranch CNN-BiLSTM model for human activity recognition using wearable sensor data
Human activity recognition (HAR) has become a significant area of research in human
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …
behavior analysis, human–computer interaction, and pervasive computing. Recently, deep …
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 …
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 …
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 …
[HTML][HTML] A state-of-the-art survey on deep learning theory and architectures
In recent years, deep learning has garnered tremendous success in a variety of application
domains. This new field of machine learning has been growing rapidly and has been …
domains. This new field of machine learning has been growing rapidly and has been …
Human activity recognition using tools of convolutional neural networks: A state of the art review, data sets, challenges, and future prospects
Abstract Human Activity Recognition (HAR) plays a significant role in the everyday life of
people because of its ability to learn extensive high-level information about human activity …
people because of its ability to learn extensive high-level information about human activity …
A review of multimodal human activity recognition with special emphasis on classification, applications, challenges and future directions
Human activity recognition (HAR) is one of the most important and challenging problems in
the computer vision. It has critical application in wide variety of tasks including gaming …
the computer vision. It has critical application in wide variety of tasks including gaming …
Multiscale deep feature learning for human activity recognition using wearable sensors
Deep convolutional neural networks (CNNs) achieve state-of-the-art performance in
wearable human activity recognition (HAR), which has become a new research trend in …
wearable human activity recognition (HAR), which has become a new research trend in …