4 citations · 8 across the 8 of their papers we have counts for
9 papers
A Review on Quantum Satellite Communications: Challenges and Future Directions
Omar Alnaseri, Yassine Himeur, Ahmed Al Asadi +4
Quantum satellite communication (QSC) is emerging as a strategic technology for secure global networking and long-distance quantum connectivity. This review prioritizes the major c…
A Novel Hybrid Deep Learning and Chaotic Dynamics Approach for Thyroid Cancer Classification
Nada Bouchekout, Abdelkrim Boukabou, Morad Grimes +5
Timely and accurate diagnosis is crucial in addressing the global rise in thyroid cancer, ensuring effective treatment strategies and improved patient outcomes. We present an intel…
LLM-Augmented and Fair Machine Learning Framework for University Admission Prediction
Mohammad Abbadi, Yassine Himeur, Shadi Atalla +2
Universities face surging applications and heightened expectations for fairness, making accurate admission prediction increasingly vital. This work presents a comprehensive framewo…
Leveraging Transfer Learning and Mobile-enabled Convolutional Neural Networks for Improved Arabic Handwritten Character Recognition
Mohsine El Khayati, Ayyad Maafiri, Yassine Himeur +3
The study explores the integration of transfer learning (TL) with mobile-enabled convolutional neural networks (MbNets) to enhance Arabic Handwritten Character Recognition (AHCR).…
Interpretable Deep Transfer Learning for Breast Ultrasound Cancer Detection: A Multi-Dataset Study
Mohammad Abbadi, Yassine Himeur, Shadi Atalla +1
Breast cancer remains a leading cause of cancer-related mortality among women worldwide. Ultrasound imaging, widely used due to its safety and cost-effectiveness, plays a key role…
Complexity of Post-Quantum Cryptography in Embedded Systems and Its Optimization Strategies
Omar Alnaseri, Yassine Himeur, Shadi Atalla +1
With the rapid advancements in quantum computing, traditional cryptographic schemes like Rivest-Shamir-Adleman (RSA) and elliptic curve cryptography (ECC) are becoming vulnerable,…
End-to-End Deep Learning in Phase Noisy Coherent Optical Link
Omar Alnaseri, Yassine Himeur
In coherent optical orthogonal frequency-division multiplexing (CO-OFDM) fiber communications, a novel end-to-end learning framework to mitigate Laser Phase Noise (LPN) impairments…
A Review on Deep Learning Autoencoder in the Design of Next-Generation Communication Systems
Omar Alnaseri, Laith Alzubaidi, Yassine Himeur +3
Traditional mathematical models used in designing next-generation communication systems often fall short due to inherent simplifications, narrow scope, and computational limitation…
Deep Learning Autoencoders for Reducing PAPR in Coherent Optical Systems
Omar Alnaseri, Ibtesam R. K. Al-Saedi, Yassine Himeur +1
This paper presents an innovative approach to mitigating the peak-to-average power ratio (PAPR). The proposed method uses a deep learning model called autoencoders (AEs) to simplif…