[HTML][HTML] Internet of things with deep learning techniques for pandemic detection: A comprehensive review of current trends and open issues

SA Ajagbe, P Mudali, MO Adigun - Electronics, 2024 - mdpi.com
Technological advancements for diverse aspects of life have been made possible by the
swift development and application of Internet of Things (IoT) based technologies. IoT …

[HTML][HTML] Enhanced random vector functional link based on artificial protozoa optimizer to predict wear characteristics of Cu-ZrO2 nanocomposites

MI Elamy, M Abd Elaziz, MA Al-Betar, A Fathy… - Results in …, 2024 - Elsevier
Owing to the absence of scientific methods for predicting nanocomposites' wear rates, a
freshly updated machine learning method that uses an Artificial Protozoa Optimizer (APO) to …

Intrusion detection: a comparison study of machine learning models using unbalanced dataset

SA Ajagbe, JB Awotunde, H Florez - SN Computer Science, 2024 - Springer
The worldwide process of converting most activities of both corporate and non-corporate
entities into digital formats is now firmly established. Machine learning models are …

Associations between fear of COVID-19 and mental health in Ghana: A sequential mediation model

J Ye, PC Huang, ES Adjaottor, FM Addo, MD Griffiths… - Heliyon, 2025 - cell.com
Introduction Although the coronavirus disease 2019 (COVID-19) pandemic has ceased
globally, individuals may still suffer from various psychological burdens in the post-COVID …

[HTML][HTML] Environmental impacts of economic growth: A STIRPAT analysis using machine learning algorithms

J Krishnendu, B Patra - Sustainable Futures, 2025 - Elsevier
This study examines the environmental consequences of economic growth using four key
dimensions–carbon dioxide emissions, freshwater availability, forest area and biodiversity …

White shark optimizer via support vector machine for video-based gender classification system

MO Oyediran, SA Ajagbe, OS Ojo, R Alshahrani… - Multimedia Tools and …, 2025 - Springer
Gender identification from videos is a challenging task with significant real-world
applications, such as video content analysis and social behavior research. In this study, we …

Assessing Data-Driven of Discriminative Deep Learning Models in Classification Task Using Synthetic Pandemic Dataset

SA Ajagbe, P Mudali, MO Adigun - Southern African Conference for …, 2024 - Springer
Deep learning models' exploration of synthetic data has been comparatively understudied
compared to other areas of research. This paper proposes an assessment of discriminative …

Deep Learning Techniques for Oral Cancer Detection: Enhancing Clinical Diagnosis by ResNet and DenseNet Performance

P Ormeño-Arriagada, E Navarro, C Taramasco… - … Conference on Applied …, 2024 - Springer
This study aims to enhance the accuracy and efficiency of oral cancer diagnosis through the
application of deep learning techniques in medical image analysis. The research employs …

[PDF][PDF] An Empirical Assessment of Discriminative Deep Learning Models for Multiclassification of COVID-19 X-rays

SA Ajagbe, P Mudali, MO Adigun - 2024 - ceur-ws.org
The current era of pandemic and infectious diseases demands contemporary technologies
across many industries. Modern inventions and technology have advanced significantly …

Telecommunication Customer Churn with Responsible AI: A Predictive Model Debugging and Business Decision Making

N Raheem, SA Ajagbe, OF Afe, IN Ezeji… - Artificial Intelligence …, 2024 - Springer
Customer churn means a customer stop doing business with telecommunication, that is not
using the service of the company again after using it for a specific period. Acquiring new …