Toyota smarthome: Real-world activities of daily living
The performance of deep neural networks is strongly influenced by the quantity and quality
of annotated data. Most of the large activity recognition datasets consist of data sourced from …
of annotated data. Most of the large activity recognition datasets consist of data sourced from …
Fully convolutional network bootstrapped by word encoding and embedding for activity recognition in smart homes
Activity recognition in smart homes is essential when we wish to propose automatic services
for the inhabitants. However, it is a challenging problem in terms of environments' variability …
for the inhabitants. However, it is a challenging problem in terms of environments' variability …
A fine-tuning based approach for daily activity recognition between smart homes
Y Yu, K Tang, Y Liu - Applied Sciences, 2023 - mdpi.com
Daily activity recognition between different smart home environments faces some
challenges, such as an insufficient amount of data and differences in data distribution …
challenges, such as an insufficient amount of data and differences in data distribution …
DeActive: scaling activity recognition with active deep learning
Deep learning architectures have been applied increasingly in multi-modal problems which
has empowered a large number of application domains needing much less human …
has empowered a large number of application domains needing much less human …
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 …
DeepMV: Multi-view deep learning for device-free human activity recognition
Recently, significant efforts are made to explore device-free human activity recognition
techniques that utilize the information collected by existing indoor wireless infrastructures …
techniques that utilize the information collected by existing indoor wireless infrastructures …
Vpn: Learning video-pose embedding for activities of daily living
In this paper, we focus on the spatio-temporal aspect of recognizing Activities of Daily Living
(ADL). ADL have two specific properties (i) subtle spatio-temporal patterns and (ii) similar …
(ADL). ADL have two specific properties (i) subtle spatio-temporal patterns and (ii) similar …
Joint learning of temporal models to handle imbalanced data for human activity recognition
Human activity recognition has become essential to a wide range of applications, such as
smart home monitoring, health-care, surveillance. However, it is challenging to deliver a …
smart home monitoring, health-care, surveillance. However, it is challenging to deliver a …
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 …
Deepsense: Device-free human activity recognition via autoencoder long-term recurrent convolutional network
In the era of Internet of Things (IoT), human activity recognition is becoming the vital
underpinning for a myriad of emerging applications in smart home and smart buildings …
underpinning for a myriad of emerging applications in smart home and smart buildings …