Deep BiLSTM Attention Model for Spatial and Temporal Anomaly Detection in Video Surveillance

Deep BiLSTM Attention Model for Spatial and Temporal Anomaly Detection in Video Surveillance

Detection of anomalies in video surveillance plays a key role in ensuring the safety and security of public spaces. The number of surveillance cameras is growing, making it harder to monitor them manually. So, automated systems are needed. This change increases the demand for automated systems that...

Full description

Saved in:
Bibliographic Details
Main Authors: Sarfaraz Natha, Fareed Ahmed, Mohammad Siraj, Mehwish Lagari, Majid Altamimi, Asghar Ali Chandio
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Sensors
Subjects:
convolutional neural network
recurrent neural network
BiLSTM
multi-attention layer
anomaly detection
Online Access:https://www.mdpi.com/1424-8220/25/1/251
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.mdpi.com/1424-8220/25/1/251

Similar Items