A Review of Anomaly Detection Techniques Using Computer Vision

[1]  Christopher Leckie,et al.  High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning , 2016, Pattern Recognit..

[2]  Shuyu Chen,et al.  An Anomaly Detection Algorithm of Cloud Platform Based on Self-Organizing Maps , 2016 .

[3]  Fiorella Lauro,et al.  Fault detection analysis using data mining techniques for a cluster of smart office buildings , 2015, Expert Syst. Appl..

[4]  Stuart J. Russell,et al.  Research Priorities for Robust and Beneficial Artificial Intelligence , 2015, AI Mag..

[5]  M. Haghi,et al.  Wearable Devices in Medical Internet of Things: Scientific Research and Commercially Available Devices , 2017, Healthcare informatics research.

[6]  Himansu Sekhar Behera,et al.  Fuzzy C-Means (FCM) Clustering Algorithm: A Decade Review from 2000 to 2014 , 2015 .

[7]  Rupert Seidl,et al.  Searching for resilience: addressing the impacts of changing disturbance regimes on forest ecosystem services. , 2016, The Journal of applied ecology.

[8]  Hui Li,et al.  Computer vision and deep learning–based data anomaly detection method for structural health monitoring , 2019 .

[9]  Manel Guerrero Zapata,et al.  A fuzzy anomaly detection system based on hybrid PSO-Kmeans algorithm in content-centric networks , 2015, Neurocomputing.

[10]  Ramesh Raskar,et al.  Computer vision uncovers predictors of physical urban change , 2017, Proceedings of the National Academy of Sciences.

[11]  Aidong Men,et al.  A Hybrid Semi-Supervised Anomaly Detection Model for High-Dimensional Data , 2017, Comput. Intell. Neurosci..

[12]  Ralph Grishman,et al.  Event Detection and Domain Adaptation with Convolutional Neural Networks , 2015, ACL.

[13]  Sutrisno Ibrahim,et al.  A comprehensive review on intelligent surveillance systems , 2016 .

[14]  Mohiuddin Ahmed,et al.  A survey of network anomaly detection techniques , 2016, J. Netw. Comput. Appl..

[15]  Jinoh Kim,et al.  A survey of deep learning-based network anomaly detection , 2017, Cluster Computing.

[16]  Jasmin Kevric,et al.  An effective combining classifier approach using tree algorithms for network intrusion detection , 2017, Neural Computing and Applications.

[17]  Javed Akhtar Khan,et al.  Improving Intrusion Detection System Based on KNN and KNN-DS with detection of U2R, R2L attack for Network Probe Attack Detection , 2016 .

[18]  Dewan Md. Farid,et al.  Application of Machine Learning Approaches in Intrusion Detection System: A Survey , 2015 .

[19]  Huihui Yu,et al.  A real time expert system for anomaly detection of aerators based on computer vision and surveillance cameras , 2020, J. Vis. Commun. Image Represent..

[20]  Stefan Axelsson,et al.  A review of computer simulation for fraud detection research in financial datasets , 2016, 2016 Future Technologies Conference (FTC).