activity
20182021
most citedSpatiotemporal Tensor Completion for Improved Urban Traffic Imputation

50 citations · 75 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG202150 cited

Spatiotemporal Tensor Completion for Improved Urban Traffic Imputation

Ahmed Ben Said, Abdelkarim Erradi

Effective management of urban traffic is important for any smart city initiative. Therefore, the quality of the sensory traffic data is of paramount importance. However, like any s…

cs.SI20201 cited

Predicting COVID-19 cases using Bidirectional LSTM on multivariate time series

Ahmed Ben Said, Abdelkarim Erradi, Hussein Aly +1

Background: To assist policy makers in taking adequate decisions to stop the spread of COVID-19 pandemic, accurate forecasting of the disease propagation is of paramount importance…

cs.LG201824 cited

Cluster validity index based on Jeffrey divergence

Ahmed Ben Said, Rachid Hadjidj, Sebti Foufou

Cluster validity indexes are very important tools designed for two purposes: comparing the performance of clustering algorithms and determining the number of clusters that best fit…

cs.CY2018

Mobile Crowdsourced Sensors Selection for Journey Services

Ahmed Ben Said, Abdelkarim Erradi, Azadeh Ghari Neiat +1

We propose a mobile crowdsourced sensors selection approach to improve the journey planning service especially in areas where no wireless or vehicular sensors are available. We dev…

cs.LG2018

A Deep Learning Spatiotemporal Prediction Framework for Mobile Crowdsourced Services

Ahmed Ben Said, Abdelkarim Erradi, Azadeh Ghari Neiat +1

This papers presents a deep learning-based framework to predict crowdsourced service availability spatially and temporally. A novel two-stage prediction model is introduced based o…