5 citations · 12 across the 15 of their papers we have counts for
15 papers
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…
Multimodal Crowd Counting with Pix2Pix GANs
Muhammad Asif Khan, Hamid Menouar, Ridha Hamila
Most state-of-the-art crowd counting methods use color (RGB) images to learn the density map of the crowd. However, these methods often struggle to achieve higher accuracy in dense…
Curriculum for Crowd Counting -- Is it Worthy?
Muhammad Asif Khan, Hamid Menouar, Ridha Hamila
Recent advances in deep learning techniques have achieved remarkable performance in several computer vision problems. A notably intuitive technique called Curriculum Learning (CL)…
Crowd Counting in Harsh Weather using Image Denoising with Pix2Pix GANs
Muhammad Asif Khan, Hamid Menouar, Ridha Hamila
Visual crowd counting estimates the density of the crowd using deep learning models such as convolution neural networks (CNNs). The performance of the model heavily relies on the q…
Visual Crowd Analysis: Open Research Problems
Muhammad Asif Khan, Hamid Menouar, Ridha Hamila
Over the last decade, there has been a remarkable surge in interest in automated crowd monitoring within the computer vision community. Modern deep-learning approaches have made it…
LCDnet: A Lightweight Crowd Density Estimation Model for Real-time Video Surveillance
Muhammad Asif Khan, Hamid Menouar, Ridha Hamila
Automatic crowd counting using density estimation has gained significant attention in computer vision research. As a result, a large number of crowd counting and density estimation…
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…
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…
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-…
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…
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…
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…
A Survey on Mobile Edge Computing for Video Streaming: Opportunities and Challenges
Muhammad Asif Khan, Emna Baccour, Zina Chkirbene +4
5G communication brings substantial improvements in the quality of service provided to various applications by achieving higher throughput and lower latency. However, interactive m…
ML-based Handover Prediction and AP Selection in Cognitive Wi-Fi Networks
Muhammad Asif Khan, Ridha Hamila, Adel Gastli +2
Device mobility in dense Wi-Fi networks offers several challenges. Two well-known problems related to device mobility are handover prediction and access point selection. Due to the…
Edge Computing in IoT: A 6G Perspective
Mariam Ishtiaq, Nasir Saeed, Muhammad Asif Khan
Edge computing is one of the key driving forces to enable Beyond 5G (B5G) and 6G networks. Due to the unprecedented increase in traffic volumes and computation demands of future ne…