no code implementations • 31 Jan 2024 • Layth Hamad, Muhammad Asif Khan, Hamid Menouar, Fethi Filali, Amr Mohamed
This paper presents Haris, an advanced autonomous mobile robot system for tracking the location of vehicles in crowded car parks using license plate recognition.
no code implementations • 15 Jan 2024 • Muhammad Asif Khan, Hamid Menouar, Ridha Hamila
In this work, we investigate the impact of curriculum learning in crowd counting using the density estimation method.
no code implementations • 15 Jan 2024 • Muhammad Asif Khan, Hamid Menouar, Ridha Hamila
Recently, some studies have reported improvement in the accuracy of crowd counting models using a combination of RGB and thermal images.
no code implementations • 11 Oct 2023 • 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).
no code implementations • 21 Aug 2023 • Muhammad Asif Khan, Hamid Menouar, Ridha Hamila
However, despite the magnitude of the issue at hand, the significant technological advancements, and the consistent interest of the research community, there are still numerous challenges that need to be overcome.
no code implementations • 10 Feb 2023 • Muhammad Asif Khan, Hamid Menouar, Ridha Hamila
These models have achieved good accuracy over benchmark datasets.
no code implementations • 2 Dec 2022 • Muhammad Asif Khan, Ridha Hamila, Hamid Menouar
CLIP combines two data-centric approaches i. e., curriculum learning and dataset pruning to improve the model learning accuracy and convergence speed.
no code implementations • 2 Dec 2022 • 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 unseen images.
no code implementations • 2 Dec 2022 • Muhammad Asif Khan, Hamid Menouar, Osama Muhammad Khalid, Adnan Abu-Dayya
Owing to the limitations of these schemes, we present a novel encryption-based drone detection scheme that uses a two-stage verification of the drone's received signal strength indicator (RSSI) and the encryption key generated from the drone's position coordinates to reliably detect an unauthorized drone in the presence of authorized drones.
no code implementations • 14 Nov 2022 • 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.
no code implementations • 14 Sep 2022 • Muhammad Asif Khan, Hamid Menouar, Ridha Hamila
In this paper, we present a systematic and comprehensive review of the most significant contributions in the area of crowd counting.
1 code implementation • 23 Apr 2022 • Wei Shao, Zhiling Jin, Shuo Wang, Yufan Kang, Xiao Xiao, Hamid Menouar, Zhaofeng Zhang, Junshan Zhang, Flora Salim
To address these issues, we construct new graph models to represent the contextual information of each node and the long-term spatio-temporal data dependency structure.
no code implementations • 17 Aug 2020 • Soufien Hamrouni, Hakim Ghazzai, Hamid Menouar, Yahya Massoud
In this paper, we propose an accurate monitoring system composed of two concatenated convolutional deep learning architectures.