Ayman A. El‐Saleh

Review of Masked Face Recognition Based on Deep Learning

Bilal Saoud, Abdul Hakim H. M. Mohamed, Ibraheem Abdullah Mohammed Shayea, Ayman A. El‐Saleh et autres

With the widespread adoption of face masks due to global health crises and heightened security concerns, traditional face recognition systems have struggled to maintain accuracy, prompting significant research into masked face recognition (MFR). Although various models have been proposed, a comprehensive and …

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Machine learning for handover decision with mobile edge computing in 6G mobile network: a survey

Soule Issa Loutfi, Ibraheem Abdullah Mohammed Shayea, Ufuk Türeli, Ayman A. El‐Saleh et autres

The forthcoming Six-Generation (6G) cellular network promises to provide novel developments in network architecture, offering greater data rates and ultra-low latency, ensuring seamless and reliable connectivity with a high quality of service for a massive number of connected devices. Even though efficient …

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Handover decision with multi-access edge computing in 6G networks: A survey

Saeid Jahandar, Ibraheem Abdullah Mohammed Shayea, Emre Güreş, Ayman A. El‐Saleh et autres

Multi-Access Edge Computing (MEC) is a key technology in the evolution of mobile networks, especially for fifth and sixth generation (5G and 6G). MEC optimises communication and computational resources by hosting application processes close to the user equipment (UE) at the network …

Harnessing Machine Learning for Intelligent Networking in 5G Technology and Beyond: Advancements, Applications and Challenges

Kristi Dulaj, Abdulraqeb Alhammadi, Ibraheem Abdullah Mohammed Shayea, Ayman A. El‐Saleh et autres

A revolutionary age in telecommunications is being ushered in by the confluence of machine learning (ML) with fifth-generation (5G) wireless communication technologies and beyond. This research investigates ML approaches in 5G networks for adaptive spectrum usage, quality of service (QoS) management, predictive …

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A Comprehensive Review of Face Detection Techniques for Occluded Faces: Methods, Datasets, and Open Challenges

Thaer Thaher, Majdi M. Mafarja, Muhammed Saffarini, Abdul Hakim H. M. Mohamed et autres

Detecting faces under occlusion remains a significant challenge in computer vision due to variations caused by masks, sunglasses, and other obstructions. Addressing this issue is crucial for applications such as surveillance,... | Find, read and cite all the research you need on …

A Hybrid Approach for Heavily Occluded Face Detection Using Histogram of Oriented Gradients and Deep Learning Models

Thaer Thaher, Muhammed Saffarini, Majdi M. Mafarja, Abdulaziz Alashbi et autres

Face detection is a critical component in modern security, surveillance, and human-computer interaction systems, with widespread applications in smartphones, biometric access control, and public monitoring. However, detecting... | Find, read and cite all the research you need on Tech Science Press

Smart Algae Cultivation: IoT-Driven Incubators and Solar Energy for Sustainable Growth in Oman

Majan Abdullah Al Jahdhami, Bilal Saoud, Raees Khalid Abutaha, Ayman A. El‐Saleh et autres

The Internet of Things (IoT) plays a crucial role in simplifying life by connecting devices and systems to monitor and control various aspects of daily activities. In Oman, IoT has been integrated across multiple sectors to build a digitally advanced and sustainable …

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Human face localization and detection in highly occluded unconstrained environments

Abdulaziz Alashbi, Abdul Hakim H. M. Mohamed, Ayman A. El‐Saleh, Ibraheem Abdullah Mohammed Shayea et autres

Significant advancements have been achieved in the field of computer vision pertaining to the detection of human faces. This technological development holds great potential for a wide range of applications including but not limited to identification, surveillance and expression recognition. Unconstrained face …

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Edge computing in future wireless networks: A comprehensive evaluation and vision for 6G and beyond

Mustafa Ergen, Bilal Saoud, Ibraheem Abdullah Mohammed Shayea, Ayman A. El‐Saleh et autres

Advancing Fetal Heart Rate Monitoring: AI-Based Approach for Baseline Detection and Classification

Abdulaziz Alashbi, Adzmely Mansor, Abdul Hakim H. M. Mohamed, Ibraheem Abdullah Mohammed Shayea et autres

Automated fetal heart rate monitoring (fhr) plays a crucial role in minimizing inconsistencies among experts, thereby reducing harmful birth complications and unnecessary medical procedures. This research proposes an algorithm for dynamic calculation of baseline variability through the utilization of an exponential moving …

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An overview of mobility awareness with mobile edge computing over 6G network: Challenges and future research directions

Soule Issa Loutfi, Ibraheem Abdullah Mohammed Shayea, Ufuk Türeli, Ayman A. El‐Saleh et autres

The evolution of science has given rise to many technologies that have changed the world. The upcoming Six-Generation (6G) mobile network indicates a fundamental transformation in wireless technologies, enhancing connectivity and data transmission rates. In this circumstance, Mobile Edge Computing (MEC) is …

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An Experimental Study on 5G Mobility Management: A Drive Test Approach

Ayman A. El‐Saleh, Abdulraqeb Alhammadi, Majan Abdullah Al Jahdhami, Adnan Kabbani et autres

Drive testing plays a crucial role in assessing and optimizing the performance of mobile networks for operators. With the transition from fourth-generation (4G) to fifth-generation (5G) networks, it becomes essential to evaluate and compare the performance of these technologies in real-world scenarios. …

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