Yazar "Elwiya, L." seçeneğine göre listele

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    ML/AI Empowered 5G and beyond Networks
    (Institute of Electrical and Electronics Engineers Inc., 2022) Al-Khafaji, M.; Elwiya, L.
    The emergence of wireless communication systems heralds the development of new technologies such as virtual reality, autonomous vehicles, Internet of things, autonomous robots and unmanned aerial systems. These advanced technologies call for high transfer rates, high reliability and, extremely low latency. These requirements may be promised by the fifth generation to meet them all. The fifth generation cannot meet these requirements without the use of artificial intelligence technology, it is expected that the fifth generation networks will generate unprecedented traffic, which in turn will enable wireless research designers to access large data that helps to predict the demands of users. Many researchers have applied artificial intelligence techniques to several ways of 5G network design like cybersecurity, network management and radio resource allocation. A deep inspection of artificial intelligence technology for the fifth generation of wireless communication systems will be conducted within this paper. This paper aims to conduct survey on the use of artificial intelligence technology within the fifth-generation wireless networks via reviewing several subjects and highlighting the difficulties associated with them, in addition to mentioning some future research directions in fifth-generation wireless communications. © 2022 IEEE.
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    Retinal Fundus Images of Optical Disk Detection
    (Institute of Electrical and Electronics Engineers Inc., 2021) Elwiya, L.; Mohammed, A.H.; Jasim, Z.K.J.
    Optical circle identification (OD) is a significant advance in the programmed division and investigation of pictures of the retina. In this article, another approach is proposed for recognizing RE cutoff points from shading retinal fundus pictures. Morphological factors and differentiation improvement methods are utilized related to a Gaussian contrast (DOG) channel to acquire an OD limit. Our proposed calculation makes a high progress rate with comparative computational time. The exhibition of our proposed strategy was assessed on 1660 pictures addressing six freely accessible informational collections; STARE, DRIVE, ARIA, DIARETDB1, DIARETDB0, and MESSIDOR informational indexes. The trial results show that the pictures from the DRIVE, ARIA, DIARETDB1 and DIARETDB0 datasets have a 100% achievement rate, which is superior to the precision of the most recent age techniques, which is under 99% for the ARIA, DIARETDB1 and DIARETDB0 informational indexes. While coming to 98.8% and 99.83% for the STARE and MESSIDOR datasets individually, the calculation runs with a normal computational season of 1.2 seconds. © 2021 IEEE.