An innovative approach based on machine learning to evaluate the risk factors importance in diagnosing keratoconus AD Zorto, MS Sharif, J Wall, A Brahma, AI Alzahrani, N Alalwan Informatics in Medicine Unlocked 38, 101208, 2023 | 3 | 2023 |
Effective machine learning based techniques for predicting depression MS Sharif, A Zorto, AT Kareem, R Hafidh 2022 International Conference on Innovation and Intelligence for Informatics …, 2022 | 3 | 2022 |
Enhancement techniques for improving facial recognition performance in convolutional neural networks MS Sharif, MO Afolabi, A Zorto, W Elmedany 2022 International Conference on Innovation and Intelligence for Informatics …, 2022 | 1 | 2022 |
Machine Learning-Based Techniques for Assessing Critical Factors for European Tick Abundance A Zorto, S Lansdell, M Seto, E Gobena, S Sharif, S Cutler ICCSIT 2024: 17th International Conference on Computer Science and …, 2024 | | 2024 |
Performance Evaluation of Ensemble Deep Learning Algorithms for Prediction of Pandemic Disease MS Sharif, A Zorto, ID Aluko 2023 Eleventh International Conference on Intelligent Computing and …, 2023 | | 2023 |
Utilising Convolutional Neural Networks for Pavement Distress Classification and Detection MS Sharif, DI Emiola, A Zorto, A Apeagyei 2023 International Conference on Innovation and Intelligence for Informatics …, 2023 | | 2023 |
Scalable Machine Learning Model for Highway CCTV Feed Real-Time Car Accident and Damage Detection MS Sharif, A Zorto, VK Brown, W Elmedany 2023 International Conference on Innovation and Intelligence for Informatics …, 2023 | | 2023 |
Conditional Tabular Generative Adversarial Net for Enhancing Ensemble Classifiers in Sepsis Diagnosis A Alfakeeh, MS Sharif, AD Zorto, T Pillonetto Applied Computational Intelligence and Soft Computing 2023 (1), 8819052, 2023 | | 2023 |
Insights into the Contribution of Multiple Factors on Tick Abundance Across Europe Spanning 20 Years Using Different Machine Learning Algorithms SL Lansdell, A Zorto, M Seto, EG Negera, MS Sharif, SJ Cutler Available at SSRN 4948979, 0 | | |