Applications of generative adversarial networks in anomaly detection: a systematic literature review
Anomaly detection has become an indispensable tool for modern society, applied in a wide
range of applications, from detecting fraudulent transactions to malignant brain tumors. Over …
range of applications, from detecting fraudulent transactions to malignant brain tumors. Over …
Learning sparse representation with variational auto-encoder for anomaly detection
Anomaly detection has a wide range of applications in security area such as network
monitoring and smart city/campus construction. It has become an active research issue of …
monitoring and smart city/campus construction. It has become an active research issue of …
Abnormal event detection and localization via adversarial event prediction
We present adversarial event prediction (AEP), a novel approach to detecting abnormal
events through an event prediction setting. Given normal event samples, AEP derives the …
events through an event prediction setting. Given normal event samples, AEP derives the …
Abnormal event detection from videos using a two-stream recurrent variational autoencoder
With the massive deployment of distributed video surveillance systems, the automatic
detection of abnormal events in video streams has become an urgent need. An abnormal …
detection of abnormal events in video streams has become an urgent need. An abnormal …
Deep learning approaches for video-based anomalous activity detection
The pervasive use of cameras at indoor and outdoor premises on account of recording the
activities has resulted into deluge of long video data. Such surveillance videos are …
activities has resulted into deluge of long video data. Such surveillance videos are …
A deep spatiotemporal perspective for understanding crowd behavior
Y Li - IEEE Transactions on multimedia, 2018 - ieeexplore.ieee.org
Understanding crowd behavior is a pivotal step toward urban scene analysis. This is
considered a very challenging task and has rarely been addressed to date due to the …
considered a very challenging task and has rarely been addressed to date due to the …
Mobile Trajectory Anomaly Detection: Taxonomy, Methodology, Challenges, and Directions
The growing number of cars on city roads has led to an increase in traffic accidents,
highlighting the need for traffic safety measures. Mobile trajectory anomaly detection is an …
highlighting the need for traffic safety measures. Mobile trajectory anomaly detection is an …
Vehicle anomalous trajectory detection algorithm based on road network partition
X Zhao, J Su, J Cai, H Yang, T Xi - Applied Intelligence, 2022 - Springer
In the process of carrying passengers, taxi drivers may have fraud problems. To solve the
problem, we propose an abnormal trajectory detection algorithm (RNPAT) via road network …
problem, we propose an abnormal trajectory detection algorithm (RNPAT) via road network …
A Survey of Deep Learning Solutions for Anomaly Detection in Surveillance Videos
JG Munyua, GM Wambugu, ST Njenga - 2021 - repository.mut.ac.ke
Deep learning has proven to be a landmark computing approach to the computer vision
domain. Hence, it has been widely applied to solve complex cognitive tasks like the …
domain. Hence, it has been widely applied to solve complex cognitive tasks like the …
Fully convolutional transformer based generative adversarial networks
Systems and methods for detecting anomaly in video data are provided. The system
includes a generator that receives past video frames and extracts spatio-temporal features of …
includes a generator that receives past video frames and extracts spatio-temporal features of …