An Efficient Anomaly Recognition Framework Using an Attention Residual LSTM in Surveillance Videos

An Efficient Anomaly Recognition Framework Using an Attention Residual LSTM in Surveillance Videos

Video anomaly recognition in smart cities is an important computer vision task that plays a vital role in smart surveillance and public safety but is challenging due to its diverse, complex, and infrequent occurrence in real-time surveillance environments. Various deep learning models use significan...

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Bibliographic Details
Main Authors: Waseem Ullah, Amin Ullah, Tanveer Hussain, Zulfiqar Ahmad Khan, Sung Wook Baik
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Sensors
Subjects:
anomaly detection
video surveillance system
abnormal activity recognition
attention mechanism
LSTM
residual LSTM
Online Access:https://www.mdpi.com/1424-8220/21/8/2811

Internet

https://www.mdpi.com/1424-8220/21/8/2811

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