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 …
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 …
Human activity recognition in a smart home environment with stacked denoising autoencoders
Activity recognition is an important step towards automatically measuring the functional
health of individuals in smart home settings. Since the inherent nature of human activities is …
health of individuals in smart home settings. Since the inherent nature of human activities is …
On-device deep learning inference for efficient activity data collection
N Mairittha, T Mairittha, S Inoue - Sensors, 2019 - mdpi.com
Labeling activity data is a central part of the design and evaluation of human activity
recognition systems. The performance of the systems greatly depends on the quantity and …
recognition systems. The performance of the systems greatly depends on the quantity and …
Activities of daily living recognition with binary environment sensors using deep learning: A comparative study
The power of end-to-end deep learning techniques to automatically learn latent high-level
features from raw signals has been demonstrated in numerous application fields, however …
features from raw signals has been demonstrated in numerous application fields, however …
Understanding and improving deep neural network for activity recognition
L Xue, S Xiandong, N Lanshun, L Jiazhen… - arXiv preprint arXiv …, 2018 - arxiv.org
Activity recognition has become a popular research branch in the field of pervasive
computing in recent years. A large number of experiments can be obtained that activity …
computing in recent years. A large number of experiments can be obtained that activity …
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 …
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 …
Activity recognition from multi-modal sensor data using a deep convolutional neural network
Multi-modal data extracted from different sensors in a smart home can be fused to build
models that recognize the daily living activities of residents. This paper proposes a Deep …
models that recognize the daily living activities of residents. This paper proposes a Deep …
Human activity recognition from multiple sensors data using deep CNNs
Smart devices with sensors now enable continuous measurement of activities of daily living.
Accordingly, various human activity recognition (HAR) experiments have been carried out …
Accordingly, various human activity recognition (HAR) experiments have been carried out …