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 …
Efficacy of imbalanced data handling methods on deep learning for smart homes environments
Human activity recognition as an engineering tool as well as an active research field has
become fundamental to many applications in various fields such as health care, smart home …
become fundamental to many applications in various fields such as health care, smart home …
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 …
Latent feature learning for activity recognition using simple sensors in smart homes
Activity recognition is an important step towards monitoring and evaluating the functional
health of an individual, and it potentially promotes human-centric ubiquitous applications in …
health of an individual, and it potentially promotes human-centric ubiquitous applications in …
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 …
ST-DeepHAR: Deep learning model for human activity recognition in IoHT applications
M Abdel-Basset, H Hawash… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Human activity recognition (HAR) has been regarded as an indispensable part of many
smart home systems and smart healthcare applications. Specifically, HAR is of great …
smart home systems and smart healthcare applications. Specifically, HAR is of great …
HARBIC: Human activity recognition using bi-stream convolutional neural network with dual joint time–frequency representation
Human activity recognition (HAR) based on wearable devices has progressively advanced
in context-aware computing like healthcare, smart homes, and industry 4.0. Since machine …
in context-aware computing like healthcare, smart homes, and industry 4.0. Since machine …
A deep machine learning method for concurrent and interleaved human activity recognition
Human activity recognition has become an important research topic within the field of
pervasive computing, ambient assistive living (AAL), robotics, health-care monitoring, and …
pervasive computing, ambient assistive living (AAL), robotics, health-care monitoring, and …
Enhancement of human complex activity recognition using wearable sensors data with inceptiontime network
P Jantawong, A Jitpattanakul… - 2021 2nd International …, 2021 - ieeexplore.ieee.org
Effective human activity recognition can be incredibly beneficial in big data applications like
ambient healthcare-supported living. Deep learning (DL) techniques have considerably …
ambient healthcare-supported living. Deep learning (DL) techniques have considerably …
Embracenet for activity: A deep multimodal fusion architecture for activity recognition
Human activity recognition using multiple sensors is a challenging but promising task in
recent decades. In this paper, we propose a deep multimodal fusion model for activity …
recent decades. In this paper, we propose a deep multimodal fusion model for activity …