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 …
A review of convolutional-neural-network-based action recognition
G Yao, T Lei, J Zhong - Pattern Recognition Letters, 2019 - Elsevier
Video action recognition is widely applied in video indexing, intelligent surveillance,
multimedia understanding, and other fields. Recently, it was greatly improved by …
multimedia understanding, and other fields. Recently, it was greatly improved by …
Deep learning in neural networks: An overview
J Schmidhuber - Neural networks, 2015 - Elsevier
In recent years, deep artificial neural networks (including recurrent ones) have won
numerous contests in pattern recognition and machine learning. This historical survey …
numerous contests in pattern recognition and machine learning. This historical survey …
Deep learning in robotics: a review of recent research
HA Pierson, MS Gashler - Advanced Robotics, 2017 - Taylor & Francis
Advances in deep learning over the last decade have led to a flurry of research in the
application of deep artificial neural networks to robotic systems, with at least 30 papers …
application of deep artificial neural networks to robotic systems, with at least 30 papers …
3D convolutional neural networks for human action recognition
We consider the automated recognition of human actions in surveillance videos. Most
current methods build classifiers based on complex handcrafted features computed from the …
current methods build classifiers based on complex handcrafted features computed from the …
A deep-learning based feature hybrid framework for spatiotemporal saliency detection inside videos
Although research on detection of saliency and visual attention has been active over recent
years, most of the existing work focuses on still image rather than video based saliency. In …
years, most of the existing work focuses on still image rather than video based saliency. In …
Automated deep learning: Neural architecture search is not the end
Deep learning (DL) has proven to be a highly effective approach for developing models in
diverse contexts, including visual perception, speech recognition, and machine translation …
diverse contexts, including visual perception, speech recognition, and machine translation …
Progress of human action recognition research in the last ten years: a comprehensive survey
Abstract Human Action Recognition (HAR) has achieved a remarkable milestone in the field
of computer vision. Apart from its varied applications in human–computer interactions …
of computer vision. Apart from its varied applications in human–computer interactions …
Automated monitoring for security camera networks: promise from computer vision labs
A substantial increase in the number of surveillance camera systems has not delivered the
promised deterrent effects or investigative case evidence and their usefulness has been …
promised deterrent effects or investigative case evidence and their usefulness has been …
Deep learning-based video action recognition: a review
MH Wani, AR Faridi - 2022 International Conference on …, 2022 - ieeexplore.ieee.org
Video action recognition refers to the process of recognizing human actions in a video. The
field of action recognition encompasses a wide variety of high-impact societal applications …
field of action recognition encompasses a wide variety of high-impact societal applications …