Mofadal Alymani

Orcid: 0009-0008-4830-6590

According to our database1, Mofadal Alymani authored at least 14 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Adaptive motion assisted human activity recognition for people with disabilities via osprey optimisation-based dimensionality reduction with recurrent neural network.
Signal Image Video Process., February, 2026

CORAL: cognitive optimization for robust and fair latency in non-ideal IRS-assisted UAV-MEC IoT networks.
Internet Things, 2026

2025
Enabling smart parking for smart cities using Internet of Things (IoT) and machine learning.
PeerJ Comput. Sci., 2025

2024
RNN-BiLSTM-CRF based amalgamated deep learning model for electricity theft detection to secure smart grids.
PeerJ Comput. Sci., 2024

A Practical Study of Intelligent Image-Based Mobile Robot for Tracking Colored Objects.
Comput. Mater. Continua, 2024

2023
Metaheuristics Algorithm-Based Minimization of Communication Costs in Federated Learning.
IEEE Access, 2023

Dispersal Foraging Strategy With Cuckoo Search Optimization Based Path Planning in Unmanned Aerial Vehicle Networks.
IEEE Access, 2023

Chaotic Jaya Optimization Algorithm With Computer Vision-Based Soil Type Classification for Smart Farming.
IEEE Access, 2023

2021
Radio spectrum awareness using deep learning: Identification of fading channels, signal distortions, medium access control protocols, and cellular systems.
Intell. Converged Networks, 2021

Modulation Classification in a Multipath Fading Channel Using Deep Learning: 16QAM, 32QAM and 64QAM.
Proceedings of the 30th Wireless and Optical Communications Conference, 2021

QAM Signal Classification and Timing Jitter Identification Based on Eye Diagrams and Deep Learning.
Proceedings of the 30th Wireless and Optical Communications Conference, 2021

2020
Rician K-Factor Estimation Using Deep Learning.
Proceedings of the 29th Wireless and Optical Communications Conference, 2020

Classification of QPSK Signals with Different Phase Noise Levels Using Deep Learning.
Proceedings of the 29th Wireless and Optical Communications Conference, 2020

5G Signal Identification Using Deep Learning.
Proceedings of the 29th Wireless and Optical Communications Conference, 2020


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