Human action recognition from various data modalities: A review

Z Sun, Q Ke, H Rahmani, M Bennamoun… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

Convolutional neural networks or vision transformers: Who will win the race for action recognitions in visual data?

O Moutik, H Sekkat, S Tigani, A Chehri, R Saadane… - Sensors, 2023 - mdpi.com
Understanding actions in videos remains a significant challenge in computer vision, which
has been the subject of several pieces of research in the last decades. Convolutional neural …

Expansion-squeeze-excitation fusion network for elderly activity recognition

X Shu, J Yang, R Yan, Y Song - IEEE Transactions on Circuits …, 2022 - ieeexplore.ieee.org
This work focuses on the task of elderly activity recognition, which is a challenging task due
to the existence of individual actions and human-object interactions in elderly activities …

A union of deep learning and swarm-based optimization for 3D human action recognition

H Basak, R Kundu, PK Singh, MF Ijaz, M Woźniak… - Scientific Reports, 2022 - nature.com
Abstract Human Action Recognition (HAR) is a popular area of research in computer vision
due to its wide range of applications such as surveillance, health care, and gaming, etc …

A fuzzy distance-based ensemble of deep models for cervical cancer detection

R Pramanik, M Biswas, S Sen… - Computer Methods and …, 2022 - Elsevier
Abstract Background and Objective Cervical cancer is one of the leading causes of women's
death. Like any other disease, cervical cancer's early detection and treatment with the best …

Human activity recognition using temporal convolutional neural network architecture

YA Andrade-Ambriz, S Ledesma… - Expert Systems with …, 2022 - Elsevier
In health care and other fields, the detection and recognition of human actions or activities
are essential in the context of human–robot interaction. During the last decade, many …

A fuzzy convolutional attention-based GRU network for human activity recognition

G Khodabandelou, H Moon, Y Amirat… - … Applications of Artificial …, 2023 - Elsevier
Human activity recognition has become a pillar of today intelligent Human–Computer
Interfaces as it typically provides more comfortable and ubiquitous interaction. This paper …

ET-NET: an ensemble of transfer learning models for prediction of COVID-19 infection through chest CT-scan images

R Kundu, PK Singh, M Ferrara, A Ahmadian… - Multimedia Tools and …, 2022 - Springer
The COVID-19 virus has caused a worldwide pandemic, affecting numerous individuals and
accounting for more than a million deaths. The countries of the world had to declare …

TranSkeleton: Hierarchical spatial–temporal transformer for skeleton-based action recognition

H Liu, Y Liu, Y Chen, C Yuan, B Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In skeleton-based action recognition, it has been a dominant paradigm to extract motion
features with temporal convolution and model spatial correlations with graph convolution …

Zoom transformer for skeleton-based group activity recognition

J Zhang, Y Jia, W **e, Z Tu - … on Circuits and Systems for Video …, 2022 - ieeexplore.ieee.org
Skeleton-based human action recognition has attracted increasing attention and many
methods have been proposed to boost the performance. However, these methods still …