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A Fusion of Artificial Intelligence and Internet of Things for Emerging Cyber SystemsRecognizing Unusual Activity with the Deep Learning Perspective in Crowd Segment

A Fusion of Artificial Intelligence and Internet of Things for Emerging Cyber Systems:... [The data’s unusual behavior suggests finding patterns in data that are not consistent with the expected behaviour. A developing prerequisite for more intelligent video vigilance of secure and open space utilizing shrewd vision frameworks can separate semantically significant behaviour towards the human spectator as typical behavior or anomalous behavior. Now presenting a novel-based energy approach for strange behavior recognition utilizing deep learning procedures. Utilize a versatile optical stream model to work on moving particles rather than articles and circuit highlights with data’s shape and direction. We present and incorporate numerous behavioral models for precise irregular activity recognition in a complex crowd scene. We have to use the individual behavior model, yet also different social behavior models. The test results show that our proposed technique effectively recognizes the unusual behavior in a packed scene. This paper revolves around a bunch conducts assessment which can perceive regular conduct or abnormal conduct.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Fusion of Artificial Intelligence and Internet of Things for Emerging Cyber SystemsRecognizing Unusual Activity with the Deep Learning Perspective in Crowd Segment

Part of the Intelligent Systems Reference Library Book Series (volume 210)
Editors: Kumar, Pardeep; Obaid, Ahmed Jabbar; Cengiz, Korhan; Khanna, Ashish; Balas, Valentina Emilia
Bala, Bhoomeshwar; Kadurka, Raja Shekar; Negasa, Galeta
A Fusion of Artificial Intelligence and Internet of Things for Emerging Cyber Systems — Aug 24, 2021
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Publisher
Springer International Publishing
Copyright
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
ISBN
978-3-030-76652-8
Pages
171 –181
DOI
10.1007/978-3-030-76653-5_9
Publisher site
See Chapter on Publisher Site

Abstract

[The data’s unusual behavior suggests finding patterns in data that are not consistent with the expected behaviour. A developing prerequisite for more intelligent video vigilance of secure and open space utilizing shrewd vision frameworks can separate semantically significant behaviour towards the human spectator as typical behavior or anomalous behavior. Now presenting a novel-based energy approach for strange behavior recognition utilizing deep learning procedures. Utilize a versatile optical stream model to work on moving particles rather than articles and circuit highlights with data’s shape and direction. We present and incorporate numerous behavioral models for precise irregular activity recognition in a complex crowd scene. We have to use the individual behavior model, yet also different social behavior models. The test results show that our proposed technique effectively recognizes the unusual behavior in a packed scene. This paper revolves around a bunch conducts assessment which can perceive regular conduct or abnormal conduct.]

Published: Aug 24, 2021

Keywords: Group scene; Crowd behaviour analysis; Usual activity; Behaviour recognition

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