M. Al-Imran, K. J. Rahaman, M. Rasel, and S. H. Ripon, “An Analytical Evaluation of a Deep Learning Model to Detect Network Intrusion,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12832 LNAI, pp. 129–140, 2021, doi: 10.1007/978-3-030-80253-0_12/COVER.
M. Al-Imran, N. N. Juthi, T. S. Mahi, and S. H. Khan, “Evaluation of Linear Imputation Based Pediatric Appendicitis Detection System Using Machine Learning Algorithm,” Communications in Computer and Information Science, vol. 1911 CCIS, pp. 437–450, 2024, doi: 10.1007/978-981-99-7240-1_35/COVER.
Hridoy, Kazi Mostaq, Saiful Islam Akash, Fahmida Afrose Dipti, Mahamudul Hasan, Jesan Ahammed Ovi, M. Al-Imran, and Sarwar Jahan. "Heart Disease Prediction Using Machine Learning Algorithms." In 2023 4th International Conference on Big Data Analytics and Practices (IBDAP), pp. 1-6. IEEE, 2023.
Accepted
M. Al-Imran, Sajid Faysal Fahim, Sanjida Simla, Fatin Hasnat Shakib, Md Belayet Hossain, and Sarwar Jahan, “Grapevine Leaf Disease Classification using Deep Convolutional Neural Networks” in International Conference on Advancements in Next Generation Computing and (ICNGCCT), IEEE, 2024.
Sajid Faysal Fahim, Fahmida Afrose Dipti, Z. T. Nishat, M. M. Azim, M. Al-Imran, “MobileNetV2: A proficient convolutional neural network for the Classification of Date Fruits into Genetic Varieties,” in International Conference on Machine Learning Algorithms in Science, Technology, Engineering, Management, Medical Science, Healthcare, and Advances in Machine Learning (ICMLA), 2024.
M. Al-Imran and S. H. Ripon, “Network Intrusion Detection: An Analytical Assessment Using Deep Learning and State-of-the-Art Machine Learning Models,” International Journal of Computational Intelligence Systems, vol. 14, no. 1, 2021, doi: 10.1007/s44196-021-00047-4.
