6 citations · 7 across the 5 of their papers we have counts for
5 papers
Auto-Configured Explainable Graph Neural Networks for Multi-Site Pollution Prediction
Abdelkader Dairi, Fouzi Harrou, Ying Sun
Accurate particulate matter (PM) prediction is crucial for mitigating air pollution. Graph Neural Networks (GNNs) effectively model spatiotemporal dependencies, but predefined grap…
Efficient Handwriting-Based Alzheimer,s Disease Diagnosis Using a Low-Rank Mixture of Experts Deep Learning Framework
Wu Wang, Yuang Cheng, Fouzi Harrou +1
Early and reliable detection of Alzheimer's disease (AD) is crucial for timely clinical intervention and improved patient management. It also supports the evaluation of emerging th…
Extended Hybrid Timed Petri Nets with Semi-Supervised Anomaly Detection for Switched Systems, Modelling and Fault Detection
Fatiha Hamdi, Abdelhafid Zeroual, Fouzi Harrou
Hybrid physical systems combine continuous and discrete dynamics, which can be simultaneously affected by faults. Conventional fault detection methods often treat these dynamics se…
Exploring the Magnitude-Shape Plot Framework for Anomaly Detection in Crowded Video Scenes
Zuzheng Wang, Fouzi Harrou, Ying Sun +1
Detecting anomalies in crowded video scenes is critical for public safety, enabling timely identification of potential threats. This study explores video anomaly detection within a…
Pointwise Data Depth for Univariate and Multivariate Functional Outlier Detection
Cristian F. Jimenez-Varon, Fouzi Harrou, Ying Sun
Data depth is an efficient tool for robustly summarizing the distribution of functional data and detecting potential magnitude and shape outliers. Commonly used functional data dep…