Human action recognition: A taxonomy-based survey, updates, and opportunities
Human action recognition systems use data collected from a wide range of sensors to
accurately identify and interpret human actions. One of the most challenging issues for …
accurately identify and interpret human actions. One of the most challenging issues for …
Deep learning based object detection for resource constrained devices: Systematic review, future trends and challenges ahead
Deep learning models are widely being employed for object detection due to their high
performance. However, the majority of applications that require object detection are …
performance. However, the majority of applications that require object detection are …
Human activity recognition via hybrid deep learning based model
In recent years, Human Activity Recognition (HAR) has become one of the most important
research topics in the domains of health and human-machine interaction. Many Artificial …
research topics in the domains of health and human-machine interaction. Many Artificial …
A new lightweight deep neural network for surface scratch detection
This paper aims to develop a lightweight convolutional neural network, WearNet, to realise
automatic scratch detection for components in contact sliding such as those in metal forming …
automatic scratch detection for components in contact sliding such as those in metal forming …
Attention induced multi-head convolutional neural network for human activity recognition
Deep neural networks, including convolutional neural networks (CNNs), have been widely
adopted for human activity recognition in recent years. They have attained significant …
adopted for human activity recognition in recent years. They have attained significant …
An image is worth 16x16 words, what is a video worth?
Leading methods in the domain of action recognition try to distill information from both the
spatial and temporal dimensions of an input video. Methods that reach State of the Art (SotA) …
spatial and temporal dimensions of an input video. Methods that reach State of the Art (SotA) …
Toward human activity recognition: a survey
Human activity recognition (HAR) is a complex and multifaceted problem. The research
community has reported numerous approaches to perform HAR. Along with HAR …
community has reported numerous approaches to perform HAR. Along with HAR …
A comprehensive review on vision-based violence detection in surveillance videos
Recent advancements in intelligent surveillance systems for video analysis have been a
topic of great interest in the research community due to the vast number of applications to …
topic of great interest in the research community due to the vast number of applications to …
Automatic robot Manoeuvres detection using computer vision and deep learning techniques: a perspective of internet of robotics things (IoRT)
To minimize any impediments in real-time Internet of Things (IoT)-enabled robotics
applications, this study demonstrated how to build and deploy a revolutionary framework …
applications, this study demonstrated how to build and deploy a revolutionary framework …
LSTM and GRU neural networks as models of dynamical processes used in predictive control: A comparison of models developed for two chemical reactors
This work thoroughly compares the efficiency of Long Short-Term Memory Networks
(LSTMs) and Gated Recurrent Unit (GRU) neural networks as models of the dynamical …
(LSTMs) and Gated Recurrent Unit (GRU) neural networks as models of the dynamical …