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 …
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 …
Recognizing human activities from raw accelerometer data using deep neural networks
L Zhang, X Wu, D Luo - 2015 IEEE 14th International …, 2015 - ieeexplore.ieee.org
Activity recognition from wearable sensor data has been researched for many years.
Previous works usually extracted features manually, which were hand-designed by the …
Previous works usually extracted features manually, which were hand-designed by the …
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 …
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 …
A deep learning approach to human activity recognition based on single accelerometer
Y Chen, Y Xue - … international conference on systems, man, and …, 2015 - ieeexplore.ieee.org
In this paper, we propose an acceleration-based human activity recognition method using
popular deep architecture, Convolution Neural Network (CNN). In particular, we construct a …
popular deep architecture, Convolution Neural Network (CNN). In particular, we construct a …
Improving activity recognition with context information
L Zhang, X Wu, D Luo - 2015 IEEE international conference on …, 2015 - ieeexplore.ieee.org
Activity recognition driven by sensor data has been heavily focused on in recent years,
especially as wearable sensors become more common and popular personal equipments …
especially as wearable sensors become more common and popular personal equipments …
Short-term recognition of human activities using convolutional neural networks
M Papakostas, T Giannakopoulos… - … conference on signal …, 2016 - ieeexplore.ieee.org
This paper proposes a deep learning classification method for frame-wise recognition of
human activities, using raw color (RGB) information. In particular, we present a …
human activities, using raw color (RGB) information. In particular, we present a …
A recent survey for human activity recoginition based on deep learning approach
JK Dhillon, AKS Kushwaha - 2017 fourth international …, 2017 - ieeexplore.ieee.org
Human activity recognition is an active research topic in computer vision due to its
applicability to wide range of application areas such as smart surveillance, robot learning …
applicability to wide range of application areas such as smart surveillance, robot learning …