A Robust Abnormal Behavior Detection Method Using Convolutional Neural Network-Reference-Cited by-同舟云学术

A Robust Abnormal Behavior Detection Method Using Convolutional Neural Network

Published:2018-08-28 Issue: Volume: Page:37-47
ISSN:1876-1100
Container-title:Lecture Notes in Electrical Engineering
language:
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Author:

Tay Nian Chi,Connie Tee,Ong Thian Song,Goh Kah Ong Michael,Teh Pin Shen

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-13-2622-6_4

Reference21 articles.

1. Nian Chi Tay, P. S. Tay, S. W. Tay: “Deep Learning for Abnormal Behavior Detection”, in Security and Authentication: Perspectives, Management and Challenges, Nova Science Publishers, United States (2018). (ISBN: 978-1-53612-942-7).

2. Cho, S., and Kang, H.:”Abnormal behavior detection using hybrid agents in crowded scenes,” Pattern Recognition Letters, 44, 64-70. https://doi.org/10.1016/j.patrec.2013.11.017 . (2014).

3. Ko, K., and Sim, K.: “Deep convolutional framework for abnormal behavior detection in a smart surveillance system,” Engineering Applications of Artificial Intelligence, 67, 226-234. https://doi.org/10.1016/j.engappai.2017.10.001 . (2018).

4. Jogile Kuklyte: “Unusual event detection in real-world surveillance applications,” Doctoral dissertation, Dublin City University. (2014).

5. F. Nater, H. Grabner, and L. Van Gool: “Exploiting simple hierarchies for unsupervised human behavior analysis,” in Proc. IEEE Conf. Comput. Vis. Pattern Recog., Jun. 13–18, pp. 2014–2021. (2010).

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