Search Results for author: Azzedine Boukerche

Found 2 papers, 1 papers with code

Generalized Video Anomaly Event Detection: Systematic Taxonomy and Comparison of Deep Models

1 code implementation10 Feb 2023 Yang Liu, Dingkang Yang, Yan Wang, Jing Liu, Jun Liu, Azzedine Boukerche, Peng Sun, Liang Song

Video Anomaly Detection (VAD) serves as a pivotal technology in the intelligent surveillance systems, enabling the temporal or spatial identification of anomalous events within videos.

Anomaly Detection Event Detection +1

Collaborative Self Organizing Map with DeepNNs for Fake Task Prevention in Mobile Crowdsensing

no code implementations17 Feb 2022 Murat Simsek, Burak Kantarci, Azzedine Boukerche

After pre-clustered legitimate tasks are separated from the original dataset, the remaining dataset is used to train a Deep Neural Network (DeepNN) to reach the ultimate performance goal.

Data Poisoning

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