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Human activity recognition in artificial intelligence framework: a narrative review
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 …
acquisition devices such as smartphones, video cameras, and its ability to capture human …
A survey on deep learning for human activity recognition
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 …
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
Human activity recognition (HAR) technology that analyzes data acquired from various types
of sensing devices, including vision sensors and embedded sensors, has motivated the …
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
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 …
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
Today's explosively growing Internet video traffics and viewers' ever-increasing quality of
experience (QoE) demands for video streaming bring tremendous pressures to the …
experience (QoE) demands for video streaming bring tremendous pressures to the …
A comprehensive survey on deep learning methods in human activity recognition
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 …
world applications ranging from healthcare to industrial environments. As the volume of …
Learning-based resource allocation for backscatter-aided vehicular networks
Heterogeneous backscatter networks are emerging as a promising solution to address the
proliferating coverage and capacity demands of next-generation vehicular networks …
proliferating coverage and capacity demands of next-generation vehicular networks …
Deep learning for radio-based human sensing: Recent advances and future directions
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 …
(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
Human monitoring applications in indoor environments depend on accurate human
identification and activity recognition (HIAR). Single modality sensor systems have shown to …
identification and activity recognition (HIAR). Single modality sensor systems have shown to …
WiFi-based human sensing with deep learning: Recent advances, challenges, and opportunities
The rapid advancements in wireless technologies have led to numerous research studies
that provide evidence of the successful utilization of wireless signals, particularly, WiFi …
that provide evidence of the successful utilization of wireless signals, particularly, WiFi …