activity
20202024
most citedRevisiting Crowd Counting: State-of-the-art, Trends, and Future Perspectives

5 citations · 6 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2024

Accelerating Deep Learning with Fixed Time Budget

Muhammad Asif Khan, Ridha Hamila, Hamid Menouar

The success of modern deep learning is attributed to two key elements: huge amounts of training data and large model sizes. Where a vast amount of data allows the model to learn mo…

cs.RO2022

Drones-aided Asset Maintenance in Hospitals

Muhammad Asif Khan, Hamid Menouar, Ridha Hamila

The rapid outbreak of COVID-19 pandemic invoked scientists and researchers to prepare the world for future disasters. During the pandemic, global authorities on healthcare urged th…

cs.CV20221 cited

Unauthorized Drone Detection: Experiments and Prototypes

Muhammad Asif Khan, Hamid Menouar, Osama Muhammad Khalid +1

The increase in the number of unmanned aerial vehicles a.k.a. drones pose several threats to public privacy, critical infrastructure and cyber security. Hence, detecting unauthoriz…

cs.CV20225 cited

Revisiting Crowd Counting: State-of-the-art, Trends, and Future Perspectives

Muhammad Asif Khan, Hamid Menouar, Ridha Hamila

Crowd counting is an effective tool for situational awareness in public places. Automated crowd counting using images and videos is an interesting yet challenging problem that has…

cs.CV2020

An Improved Dilated Convolutional Network for Herd Counting in Crowded Scenes

Soufien Hamrouni, Hakim Ghazzai, Hamid Menouar +1

Crowd management technologies that leverage computer vision are widespread in contemporary times. There exists many security-related applications of these methods, including, but n…