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Human action recognition from various data modalities: A review
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 …
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?
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 …
has been the subject of several pieces of research in the last decades. Convolutional neural …
Expansion-squeeze-excitation fusion network for elderly activity recognition
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 …
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
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 …
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 …
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 …
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
Human activity recognition has become a pillar of today intelligent Human–Computer
Interfaces as it typically provides more comfortable and ubiquitous interaction. This paper …
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
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 …
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
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 …
features with temporal convolution and model spatial correlations with graph convolution …
Zoom transformer for skeleton-based group activity recognition
Skeleton-based human action recognition has attracted increasing attention and many
methods have been proposed to boost the performance. However, these methods still …
methods have been proposed to boost the performance. However, these methods still …