A survey on video-based human action recognition: recent updates, datasets, challenges, and applications

P Pareek, A Thakkar - Artificial Intelligence Review, 2021 - Springer
Abstract Human Action Recognition (HAR) involves human activity monitoring task in
different areas of medical, education, entertainment, visual surveillance, video retrieval, as …

Human action recognition using attention based LSTM network with dilated CNN features

K Muhammad, A Ullah, AS Imran, M Sajjad… - Future Generation …, 2021 - Elsevier
Human action recognition in videos is an active area of research in computer vision and
pattern recognition. Nowadays, artificial intelligence (AI) based systems are needed for …

Carbon emissions of 5G mobile networks in China

T Li, L Yu, Y Ma, T Duan, W Huang, Y Zhou, D Jin… - Nature …, 2023 - nature.com
Telecommunication using 5G plays a vital role in our daily lives and the global economy.
However, the energy consumption and carbon emissions of 5G mobile networks are …

Motion capture data denoising based on LSTNet autoencoder

YQ Zhu, YM Cai, F Zhang - Journal of Internet Technology, 2022 - jit.ndhu.edu.tw
This paper proposes a novel deep learning-based optical motion capture denoising model
encoder-LSTNet-decoder (ELD). ELD uses an autoencoder for manifold learning and …

Applying data mining techniques to explore user behaviors and watching video patterns in converged IT environments

YS Su, SY Wu - Journal of Ambient Intelligence and Humanized …, 2021 - Springer
Comfortable leisure and entertainment is expected through multimedia. Web multimedia
systems provide diversified multimedia interactions, for example, sharing knowledge …

Attention-based bidirectional-long short-term memory for abnormal human activity detection

M Kumar, AK Patel, M Biswas, S Shitharth - Scientific Reports, 2023 - nature.com
Abnormal human behavior must be monitored and controlled in today's technology-driven
era, since it may cause damage to society in the form of assault or web-based violence, such …

An IoT-platform-based deep learning system for human behavior recognition in smart city monitoring using the Berkeley MHAD datasets

OO Khalifa, A Roubleh, A Esgiar, M Abdelhaq… - Systems, 2022 - mdpi.com
Internet of Things (IoT) technology has been rapidly developing and has been well utilized
in the field of smart city monitoring. The IoT offers new opportunities for cities to use data …

Predicting behavioral competencies automatically from facial expressions in real-time video-recorded interviews

YS Su, HY Suen, KE Hung - Journal of Real-Time Image Processing, 2021 - Springer
This work aims to develop a real-time image and video processor enabled with an artificial
intelligence (AI) agent that can predict a job candidate's behavioral competencies according …

A low-latency object detection algorithm for the edge devices of IoV systems

C Dai, X Liu, W Chen, CF Lai - IEEE Transactions on Vehicular …, 2020 - ieeexplore.ieee.org
The emergence of edge computing (EC) and intelligent vision-based driver assistance
system is of great significance for the prospective development of Internet of Vehicle (IoV) …

Compressing deep model with pruning and tucker decomposition for smart embedded systems

C Dai, X Liu, H Cheng, LT Yang… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Deep learning has been proved to be one of the most effective method in feature encoding
for different intelligent applications such as video-based human action recognition …