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General Information
    • ISSN: 2382-6185
    • Frequency: Quarterly (2015-2016); semiyearly (Since 2017)
    • DOI: 10.18178/IJKE
    • Editor-in-Chief: Prof. Chen-Huei Chou
    • Executive Editor: Ms. Nina Lee
    • Indexed by: Google Scholar, DOAJ, Engineering & Technology Digital Library, Crossref, ProQuest
    • E-mail: ijke@ejournal.net
Editor-in-chief
Prof. Chen-Huei Chou
College of Charleston, SC, USA
It is my honor to be the editor-in-chief of IJKE. I will do my best to help develop this journal better.
IJKE 2016 Vol.2(2): 104-108 ISSN: 2382-6185
doi: 10.18178/ijke.2016.2.2.062

Anomaly Detection System for Video Data Using Machine Learning

Tadashi Ogino
Abstract—We are developing an anomaly detection system for video data that uses machine learning. The proposed system has two subsystems: feature extraction and anomaly detection. We developed two feature extraction systems. One uses traditional manual steps and the other uses machine learning, i.e., a neural network. For the anomaly detection system, we employ machine learning technology that we have developed for a cyber-attack detection system. Results confirm that both prototypes can detect anomalous events in experimental video data.

Index Terms—Anomaly detection, machine learning, video, Jubatus.

Tadashi Ogino is with School of Information Science, Meisei University, Hino, Japan (e-mail: tadashi.ogino@nifty.com).

[PDF]

Cite: Tadashi Ogino, "Anomaly Detection System for Video Data Using Machine Learning," International Journal of Knowledge Engineering vol. 2, no. 2, pp. 104-108, 2016.

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E-mail: ijke@ejournal.net