Mokhtar Keche

Accurate indoor visible light positioning method using four LEDs and a smartphone camera

Kheira Amari, Mokhtar Keche

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Textured Images Classification Using Nearest Feature Line Method Added with Kurtosis and Skewness

Tarik Boudghene Stambouli, Abdelaziz Ouamri, Mokhtar Keche

In this study, we try to compare the performances of various textured images classification methods, all based on multi resolution decompositions. The images tested are extracted from the Brodatz album. For decomposition, we use the Separable (SWT) and NonSeparable Wavelet Transforms (NSWT). …

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Road Traffic Classification from Nighttime Videos Using the Multihead Self-Attention Vision Transformer Model and the SVM

Sofiane Abdelkrim Khalladi, Asmâa Ouessai, Mokhtar Keche

Abstract Intelligent transport systems (ITSs) have emerged as a groundbreaking solution to address the challenges associated with road traffic, which are enhancing road utilization efficiency, providing convenient and safe transportation, and reducing energy consumption. ITS leverages advanced technologies to collect, store, and …

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Improving VANET Data Dissemination Efficiency with Deep Neural Networks

Ameur Bennaoui, Mustapha Guezouri, Mokhtar Keche

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Efficient phase difference–based visible light positioning system

Asmaa Hadjer Saboundji, Mokhtar Keche, Mohammed Dahmani

Visible light (VL) indoor positioning offers significant advantages, such as low cost, high durability, and environmental protection. In this work, a phase difference-based VL positioning (VLP) system is presented. It uses the fast Fourier transform to accelerate the computation of the phase …

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Deep-Learning-Based Microscopic Approach for Road Traffic Congestion Classification in Highway and Urban Roads Under Adverse Conditions

Sofiane Abdelkrim Khalladi, Asmâa Ouessai, Nadir Kamel Benamara, Mokhtar Keche

Road traffic congestion is a significant issue in urban and highway roads since it can cause various adverse effects, such as increasing travel time, elevated levels of air pollution, and a higher likelihood of traffic accidents and collisions because of congested conditions …

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A Non-Stellar Big Bright Object Elimination and Star Centroid Extraction Algorithm for Star Tracker

Zoubida Mahi, Moussa Sofiane Karoui, Mokhtar Keche

The star tracker is a highly accurate measuring instrument used in satellite attitude measurement and determination systems. Stellar images are important since they are the first key in the satellite attitude control process. In the lost-in-space case, stellar images are captured randomly …

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Efficient Road Traffic Video Congestion Classification Based on the Multi-Head Self-Attention Vision Transformer Model

Sofiane Abdelkrim Khalladi, Asmâa Ouessai, Nadir Kamel Benamara, Mokhtar Keche

Abstract Due to rapid population growth, traffic congestion has become one of the major issues in urban areas. The utilization of technology may help to address this issue. This paper proposes a new Multi-head Self-attention Vision Transformer (MSViT) based macroscopic approach, for …

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An LED Detection Algorithm for VLC System Based on an LED Matrix and a Smartphone Camera

Azil Ibrahim, Mohammed Dahmani, Mokhtar Keche

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A Hybrid Approach for WebRTC Video Streaming on Resource-Constrained Devices

Bakary Diallo, Abdelaziz Ouamri, Mokhtar Keche

This paper introduces thorough comparative and interoperability analyses involving a browser-based P2P video streaming approach utilizing WebRTC (web real-time communication), along with WebRTC hybrid solutions developed using the React Native framework (for mobile) and the electron framework (for desktop and Raspberry Pi). …

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A new star detection approach for a satellite-onboard star tracker

Zoubida Mahi, Moussa Sofiane Karoui, Mokhtar Keche

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Accurate visible light positioning system using neural network

Asmaa Hadjer Saboundji, Souhila Meziane, Mohammed Dahmani, Abdelkrim Meche et autres

Visible light indoor positioning has significant advantages, such as low cost, high durability, and environmental protection. In this paper, we investigate the use of artificial neural networks in an indoor positioning system based on visible light. The position of the receiver is …

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