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Auto-encoders in deep learning—a review with new perspectives
S Chen, W Guo - Mathematics, 2023 - mdpi.com
Deep learning, which is a subfield of machine learning, has opened a new era for the
development of neural networks. The auto-encoder is a key component of deep structure …
development of neural networks. The auto-encoder is a key component of deep structure …
Deep learning for anomaly detection: A survey
Anomaly detection is an important problem that has been well-studied within diverse
research areas and application domains. The aim of this survey is two-fold, firstly we present …
research areas and application domains. The aim of this survey is two-fold, firstly we present …
Identification of high-risk roadway segments for wrong-way driving crash using rare event modeling and data augmentation techniques
Abstract Wrong-Way Driving (WWD) crashes are relatively rare but more likely to produce
fatalities and severe injuries than other crashes. WWD crash segment prediction task is …
fatalities and severe injuries than other crashes. WWD crash segment prediction task is …
Spatio-temporal fall event detection in complex scenes using attention guided LSTM
Fall events are one of the greatest risks for public safety, especially in some complex scenes
with large number of people. Nevertheless, there are few researches on fall detection in …
with large number of people. Nevertheless, there are few researches on fall detection in …
[HTML][HTML] Unsupervised video anomaly detection based on similarity with predefined text descriptions
Research on video anomaly detection has mainly been based on video data. However,
many real-world cases involve users who can conceive potential normal and abnormal …
many real-world cases involve users who can conceive potential normal and abnormal …
Anomaly detection in surveillance video using pose estimation
A Thyagarajmurthy, MG Ninad, BG Rakesh… - Emerging Research in …, 2019 - Springer
In this paper, we focus on key points detection of a person. We judge the abnormal behavior
of the person by detecting the motion of key points of that person. In the starting frame, we …
of the person by detecting the motion of key points of that person. In the starting frame, we …
Deep reinforcement learning-based anomaly detection for video surveillance
S Aberkane, M Elarbi-Boudihir - Informatica, 2022 - informatica.si
The anomaly detection in automated video surveillance is considered as one of the most
critical tasks to be solved, in which we aim to detect a variety of real-world abnormalities …
critical tasks to be solved, in which we aim to detect a variety of real-world abnormalities …
Real-time video surveillance system for detecting malicious actions and weapons in public spaces
M Narayanan, S Jaju, A Nair, A Mhatre… - Computer Networks and …, 2021 - Springer
In today's world, thousands of surveillance cameras have been working round the clock.
These cameras are installed at railway stations, ATMs, streets and all the public spaces that …
These cameras are installed at railway stations, ATMs, streets and all the public spaces that …
Unsupervised anomaly detection of the first person in gait from an egocentric camera
Assistive technology is increasingly important as the senior population grows. The purpose
of this study is to develop a means of preventing fatal injury by monitoring the movements of …
of this study is to develop a means of preventing fatal injury by monitoring the movements of …
Mutual Learning Inspired Prediction Network for Video Anomaly Detection
Y Zhang, X Fang, F Li, L Yu - … on Pattern Recognition and Computer Vision …, 2022 - Springer
Video anomaly detection has made great achievements in security work. A basic
assumption is that the abnormal is the outlier of the normal. However, most existing methods …
assumption is that the abnormal is the outlier of the normal. However, most existing methods …