A Deep Autoencoder-Based Approach for Suspicious Action Recognition in Surveillance Videos
Author:
Funder
Higher Education Commission, Pakistan
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
https://link.springer.com/content/pdf/10.1007/s13369-023-08038-7.pdf
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3. Himeur, Y.; Ghanem, K.; Alsalemi, A.; Bensaali, F.; Amira, A.: Artificial intelligence based anomaly detection of energy consumption in buildings: a review, current trends and new perspectives. Appl. Energy 287, 116601 (2021)
4. Ruff, L.; Kauffmann, J.R.; Vandermeulen, R.A.; Montavon, G.; Samek, W.; Kloft, M.; Dietterich, T.G.; Müller, K.-R.: A unifying review of deep and shallow anomaly detection. In: Proceedings of the IEEE (2021)
5. Thudumu, S.; Branch, P.; Jin, J.; Singh, J.J.: A comprehensive survey of anomaly detection techniques for high dimensional big data. J. Big Data 7(1), 1–30 (2020)
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