| Machinery faults diagnosis using support vector machine (SVM) and Naïve Bayes classifiers MAS Al Tobi, KP Ramachandran, S Al-Araimi, R Pacturan, A Rajakannu, ... Int. J. Engi. Trends Technol. 70 (12), 26-34, 2022 | 35 | 2022 |
| Transfer learning networks with skip connections for classification of brain tumors S Alaraimi, KE Okedu, H Tianfield, R Holden, O Uthmani International Journal of Imaging Systems and Technology 31 (3), 1564-1582, 2021 | 29 | 2021 |
| A review to do fishermen boat automation with artificial intelligence for sustainable fishing experience ensuring safety, security, navigation and sharing information for Omani … R Amuthakkannan, K Vijayalakshmi, S Al Araimi, M Ali Saud Al Tobi Journal of Marine Science and Engineering 11 (3), 630, 2023 | 28 | 2023 |
| Comparative study of the effects of machine parameters on DFIG and PMSG variable speed wind turbines during grid fault KE Okedu, M Al Tobi, S Al Araimi Frontiers in Energy Research 9, 681443, 2021 | 22 | 2021 |
| Machinery Fault Diagnosis using Continuous Wavelet Transform and Artificial Intelligence based classification MAS Al Tobi, R K p, S Al-Araimi, R Pacturan, A Rajakannu, G Achuthan Proceedings of the 2022 3rd International Conference on Robotics Systems and …, 2022 | 4 | 2022 |
| Development of Heuristic Algorithm based tool to extract and evaluate tumor section from Brain MRI and CT image SM Kesavan, S Tanavade, MA Balushi, SSA Araimi, AA Khazraji 3rd Smart Cities Symposium (SCS 2020), 2021, p. 375 – 379, 2021 | 3 | 2021 |
| Enhancing Brain Tumor Assessment: A Comprehensive Approach using Computerized Diagnostic Tool and Advanced MRI Techniques S Alaraimi, I Al Naimi, S Manic, N Al Hinai, S Al Shukaili Procedia Computer Science 235, 3350-3368, 2024 | 1 | 2024 |
