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 …
The layer-wise training convolutional neural networks using local loss for sensor-based human activity recognition
Recently, deep learning, which are able to extract automatically features from data, has
achieved state-of-the-art performance across a variety of sensor based human activity …
achieved state-of-the-art performance across a variety of sensor based human activity …
Deep convolutional networks with tunable speed–accuracy tradeoff for human activity recognition using wearables
Activity recognition plays a critical role in various applications, such as medical monitoring
and rehabilitation. Deep learning has recently made great development in the wearable …
and rehabilitation. Deep learning has recently made great development in the wearable …
Human activity recognition using wearable sensors by heterogeneous convolutional neural networks
Recent researches on sensor based human activity recognition (HAR) are mostly devoted to
designing various network architectures to enhance their feature representation capacity for …
designing various network architectures to enhance their feature representation capacity for …
Real-time human activity recognition using conditionally parametrized convolutions on mobile and wearable devices
Recently, deep learning has represented an important research trend in human activity
recognition (HAR). In particular, deep convolutional neural networks (CNNs) have achieved …
recognition (HAR). In particular, deep convolutional neural networks (CNNs) have achieved …
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 …
Shallow convolutional neural networks for human activity recognition using wearable sensors
Due to rapid development of sensor technology, human activity recognition (HAR) using
wearable inertial sensors has recently become a new research hotspot. Deep learning …
wearable inertial sensors has recently become a new research hotspot. Deep learning …
A lightweight framework for human activity recognition on wearable devices
YL Coelho, FAS dos Santos, A Frizera-Neto… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Human Activity Recognition (HAR) is the automatic detection and understanding of human
motion behavior based on data extracted from video camera, ambient sensors or wearable …
motion behavior based on data extracted from video camera, ambient sensors or wearable …
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 …
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 …