Human activity recognition in artificial intelligence framework: a narrative review

N Gupta, SK Gupta, RK Pathak, V Jain… - Artificial intelligence …, 2022 - Springer
Human activity recognition (HAR) has multifaceted applications due to its worldly usage of
acquisition devices such as smartphones, video cameras, and its ability to capture human …

A survey on deep learning for human activity recognition

F Gu, MH Chung, M Chignell, S Valaee… - ACM Computing …, 2021 - dl.acm.org
Human activity recognition is a key to a lot of applications such as healthcare and smart
home. In this study, we provide a comprehensive survey on recent advances and challenges …

Sensor-based and vision-based human activity recognition: A comprehensive survey

LM Dang, K Min, H Wang, MJ Piran, CH Lee, H Moon - Pattern Recognition, 2020 - Elsevier
Human activity recognition (HAR) technology that analyzes data acquired from various types
of sensing devices, including vision sensors and embedded sensors, has motivated the …

Human activity recognition using tools of convolutional neural networks: A state of the art review, data sets, challenges, and future prospects

MM Islam, S Nooruddin, F Karray… - Computers in biology and …, 2022 - Elsevier
Abstract Human Activity Recognition (HAR) plays a significant role in the everyday life of
people because of its ability to learn extensive high-level information about human activity …

Intelligent video caching at network edge: A multi-agent deep reinforcement learning approach

F Wang, F Wang, J Liu, R Shea… - IEEE INFOCOM 2020 …, 2020 - ieeexplore.ieee.org
Today's explosively growing Internet video traffics and viewers' ever-increasing quality of
experience (QoE) demands for video streaming bring tremendous pressures to the …

A comprehensive survey on deep learning methods in human activity recognition

M Kaseris, I Kostavelis, S Malassiotis - Machine Learning and Knowledge …, 2024 - mdpi.com
Human activity recognition (HAR) remains an essential field of research with increasing real-
world applications ranging from healthcare to industrial environments. As the volume of …

Learning-based resource allocation for backscatter-aided vehicular networks

WU Khan, TN Nguyen, F Jameel… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Heterogeneous backscatter networks are emerging as a promising solution to address the
proliferating coverage and capacity demands of next-generation vehicular networks …

Deep learning for radio-based human sensing: Recent advances and future directions

I Nirmal, A Khamis, M Hassan, W Hu… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
While decade-long research has clearly demonstrated the vast potential of radio frequency
(RF) for many human sensing tasks, scaling this technology to large scenarios remained …

[HTML][HTML] Interpretable passive multi-modal sensor fusion for human identification and activity recognition

L Yuan, J Andrews, H Mu, A Vakil, R Ewing, E Blasch… - Sensors, 2022 - mdpi.com
Human monitoring applications in indoor environments depend on accurate human
identification and activity recognition (HIAR). Single modality sensor systems have shown to …

WiFi-based human sensing with deep learning: Recent advances, challenges, and opportunities

I Ahmad, A Ullah, W Choi - IEEE Open Journal of the …, 2024 - ieeexplore.ieee.org
The rapid advancements in wireless technologies have led to numerous research studies
that provide evidence of the successful utilization of wireless signals, particularly, WiFi …