Flowchart of the proposed approach.

<div><p>Surveillance systems are integral to ensuring public safety by detecting unusual incidents, yet existing methods often struggle with accuracy and robustness. This study introduces an advanced framework for anomaly recognition in surveillance, leveraging deep learning to address t...

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Bibliographic Details
Main Author:	Shaista Khanam (21387548) (author)
Other Authors:	Muhammad Sharif (7039565) (author), Mudassar Raza (17145050) (author), Waqar Ishaq (21387551) (author), Muhammad Fayyaz (7643474) (author), Seifedine Kadry (8713629) (author)
Published:	2025
Subjects:	Neuroscience Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified proposed approach achieves net ,&# 8221 leveraging deep learning ensuring public safety employs two dcnns detecting unusual incidents achieve significant improvements enhance feature visibility 2500 selected features study &# 8217 deep learning models study introduces features extracted feature extraction &# 8220 unprecedented 99 substantial leap practical real novel 63 new benchmark layer cnn innovative combination genetic algorithm ga optimizer ga ). framework begins fold cross existing methods established inception current techniques contribution lies anomaly recognition advanced framework
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Flowchart of the proposed approach.

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