An investigation of recurrent neural network for daily activity recognition using multi-modal signals
Our aim is to build a daily activity surveillance system for elderly people. In this study, we
develop Deep Neural Network (RNN) based approach for human activity recognition task by …
develop Deep Neural Network (RNN) based approach for human activity recognition task by …
Daily activity recognition with large-scaled real-life recording datasets based on deep neural network using multi-modal signals
In this study, toward the development of smartphone-based monitoring system for life
logging, we collect over 1,400 hours of data by recording including both the outdoor and …
logging, we collect over 1,400 hours of data by recording including both the outdoor and …
Daily activity recognition based on recurrent neural network using multi-modal signals
Our aim is to develop a smartphone-based life-logging system. Human activity recognition
(HAR) is one of the core techniques to realize it. Recent studies reported the effectiveness of …
(HAR) is one of the core techniques to realize it. Recent studies reported the effectiveness of …
Daily activity recognition based on DNN using environmental sound and acceleration signals
We propose a new method of recognizing daily human activities based on a Deep Neural
Network (DNN), using multimodal signals such as environmental sound and subject …
Network (DNN), using multimodal signals such as environmental sound and subject …
LSTM-RNNs combined with scene information for human activity recognition
WH Chen, CAB Baca, CH Tou - 2017 IEEE 19th International …, 2017 - ieeexplore.ieee.org
Developing an accurate activity recognition system with sensor readings is a challenging
task due to the fact that sensors are subjected to a variety of errors and the nature of human …
task due to the fact that sensors are subjected to a variety of errors and the nature of human …
Comparative study of machine learning algorithms for activity recognition with data sequence in home-like environment
Activity recognition is a key problem in multisensor systems. With data collected from
different sensors, a multi-sensor system identifies activities performed by the inhabitants …
different sensors, a multi-sensor system identifies activities performed by the inhabitants …
A deep learning approach for human activities recognition from multimodal sensing devices
Research in the recognition of human activities of daily living has significantly improved
using deep learning techniques. Traditional human activity recognition techniques often use …
using deep learning techniques. Traditional human activity recognition techniques often use …
Human activity recognition using recurrent neural networks
Human activity recognition using smart home sensors is one of the bases of ubiquitous
computing in smart environments and a topic undergoing intense research in the field of …
computing in smart environments and a topic undergoing intense research in the field of …
[HTML][HTML] Human Activity Recognition Based on Frequency-Modulated Continuous Wave and DenseNet
W Jiang, Y Ma, W Zhuang, Z Wu, Y Hua, M Li… - Journal of Computer and …, 2023 - scirp.org
With the development of wireless technology, Frequency-Modulated Continuous Wave
(FMCW) radar has increased sensing capability and can be used to recognize human …
(FMCW) radar has increased sensing capability and can be used to recognize human …
Deep neural networks for activity recognition with multi-sensor data in a smart home
J Park, K Jang, SB Yang - 2018 IEEE 4th World Forum on …, 2018 - ieeexplore.ieee.org
Multi-sensor based human activity recognition is one of the challenges in the ambient
intelligent environments such as smart home and smart city. Ordinary people in their daily …
intelligent environments such as smart home and smart city. Ordinary people in their daily …