Abnormal Event Detection in Videos using LSTM Convolutional Autoencoder

This research investigates the application of a novel LSTM Convolutional Autoencoder (LSTM-CAE) framework for video anomaly detection, utilizing the UCSD Anomaly Detection Dataset. Traditional methods in video anomaly detection often face challenges in capturing both temporal and spatial dependencie...

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Bibliographic Details

Published in:	Intelligent Systems and Computer Vision (Online) pp. 1 - 4
Main Authors:	Berroukham, Abdelhafid, Housni, Khalid, Lahraichi, Mohammed
Format:	Conference Proceeding
Language:	English
Published:	IEEE 08.05.2024
Subjects:	Anomaly detection Autoencoder Deep Learning Ensemble learning Event detection Intelligent systems LSTM Security Surveillance Transfer learning
ISSN:	2768-0754
Online Access:	Get full text
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