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20212024
most citedRevisiting Crowd Counting: State-of-the-art, Trends, and Future Perspectives

5 citations · 12 across the 15 of their papers we have counts for

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Showing 2022 · cs.CVShow all

5 papers · 2 filters

cs.CV2022★ 1 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.CV2022

CLIP: Train Faster with Less Data

Muhammad Asif Khan, Ridha Hamila, Hamid Menouar

Deep learning models require an enormous amount of data for training. However, recently there is a shift in machine learning from model-centric to data-centric approaches. In data-…

cs.CV2022

Crowd Density Estimation using Imperfect Labels

Muhammad Asif Khan, Hamid Menouar, Ridha Hamila

Density estimation is one of the most widely used methods for crowd counting in which a deep learning model learns from head-annotated crowd images to estimate crowd density in uns…

cs.CV2022★ 1 cited

DroneNet: Crowd Density Estimation using Self-ONNs for Drones

Muhammad Asif Khan, Hamid Menouar, Ridha Hamila

Video surveillance using drones is both convenient and efficient due to the ease of deployment and unobstructed movement of drones in many scenarios. An interesting application of…

cs.CV2022★ 5 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…