Zobrazeno 1 - 10
of 75
pro vyhledávání: '"Stephen Ojo"'
Autor:
Sarah A. Alzakari, Stephen Ojo, James Wanliss, Muhammad Umer, Shtwai Alsubai, Areej Alasiry, Mehrez Marzougui, Nisreen Innab
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
Accurate detection of skin lesions through computer-aided diagnosis has emerged as a critical advancement in dermatology, addressing the inefficiencies and errors inherent in manual visual analysis. Despite the promise of automated diagnostic approac
Externí odkaz:
https://doaj.org/article/a51359da3de94e8598f472f09ea83580
Autor:
Asma Aldrees, Stephen Ojo, James Wanliss, Muhammad Umer, Muhammad Attique Khan, Bayan Alabdullah, Shtwai Alsubai, Nisreen Innab
Publikováno v:
Frontiers in Computational Neuroscience, Vol 18 (2024)
Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by notable challenges in cognitive function, understanding language, recognizing objects, interacting with others, and communicating effectively. Its origins are mainly genetic,
Externí odkaz:
https://doaj.org/article/c15c2ea3c3d340b187e71715be187cfe
Publikováno v:
Frontiers in Computational Neuroscience, Vol 18 (2024)
Parkinson's disease (PD) is a globally significant health challenge, necessitating accurate and timely diagnostic methods to facilitate effective treatment and intervention. In recent years, self-supervised deep representation pattern learning (SS-DR
Externí odkaz:
https://doaj.org/article/73656e6f560b46f7b5efd8e89a4ae112
Autor:
Sidra Abbas, Stephen Ojo, Abdullah Al Hejaili, Gabriel Avelino Sampedro, Ahmad Almadhor, Monji Mohamed Zaidi, Natalia Kryvinska
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-21 (2024)
Abstract As cardiovascular disorders are prevalent, there is a growing demand for reliable and precise diagnostic methods within this domain. Audio signal-based heart disease detection is a promising area of research that leverages sound signals gene
Externí odkaz:
https://doaj.org/article/517ba2e3aa8942f6b93a0b848a249b3d
Autor:
Gabriel Avelino Sampedro, Stephen Ojo, Moez Krichen, Meznah A. Alamro, Alaeddine Mihoub, Vincent Karovic
Publikováno v:
IEEE Access, Vol 12, Pp 157408-157417 (2024)
Adversarial attacks involve manipulating data to trick Artificial Intelligence (AI) models, making false predictions or classifications or even disrupting the normal functions of the smart grid. This can be done by providing the wrong information to
Externí odkaz:
https://doaj.org/article/7a417f0d76be46be80cdb3fc37c16503
Autor:
Sidra Abbas, Stephen Ojo, Imen Bouazzi, Gabriel Avelino Sampedro, Abdullah Al Hejaili, Ahmad S. Almadhor, Rastislav Kulhanek
Publikováno v:
IEEE Access, Vol 12, Pp 138904-138920 (2024)
The widespread use of smartphones has brought convenience and connectivity to the fingertips of the masses. As a result, this has paved the way for potential security vulnerabilities concerning sensitive data, particularly by exploiting side-channel
Externí odkaz:
https://doaj.org/article/17f06f1754054ea9b51369f0a70a0a16
Publikováno v:
IEEE Access, Vol 12, Pp 76003-76021 (2024)
One of the main causes of death from cardiovascular diseases is Myocardial Infarction (MI), which is brought on by coronary artery problems. Myocardial infarction is a pathological condition resulting from an anatomical issue with the Left Ventricle
Externí odkaz:
https://doaj.org/article/76b06b6dc6bc416f9364fee99dee73f4
Autor:
Max Blose, Lateef Adesola Akinyemi, Stephen Ojo, Muhammad Faheem, Agbotiname Lucky Imoize, Arfat Ahmad Khan
Publikováno v:
IEEE Access, Vol 12, Pp 63334-63350 (2024)
The Software-Defined Networking technology promises to enhance network performance and cost reduction for service providers by providing scalability, flexibility, and programmability through the separation of the control plane from the data plane. Ho
Externí odkaz:
https://doaj.org/article/488476765a4047a884b6d69190a0a4c6
Autor:
Ahmad Almadhor, Sidra Abbas, Gabriel Avelino Sampedro, Shtwai Alsubai, Stephen Ojo, Abdullah Al Hejaili, Lubomira Strazovska
Publikováno v:
IEEE Access, Vol 12, Pp 58097-58105 (2024)
This research delves into applying active and machine learning techniques to predict student anxiety. This research explores how these technologies can be explored to understand and predict student anxiety levels. This study utilizes active learning
Externí odkaz:
https://doaj.org/article/86f429e704364ed3ba50795dec20350c
Autor:
Sidra Abbas, Gabriel Avelino Sampedro, Shtwai Alsubai, Stephen Ojo, Ahmad S. Almadhor, Abdullah Al Hejaili, Lubomira Strazovska
Publikováno v:
IEEE Access, Vol 12, Pp 44949-44959 (2024)
This research explores the potential of technologies in human activity recognition among the elderly population. More precisely, using sensor data and implementing Active Learning (AL), Machine Learning (ML), and Deep learning (DL) techniques for eld
Externí odkaz:
https://doaj.org/article/c4749961f8794a7f831b72179fb4b907