| A new benchmark on american sign language recognition using convolutional neural network MM Rahman, MS Islam, MH Rahman, R Sassi, MW Rivolta, ... 2019 International Conference on Sustainable Technologies for Industry 4.0 …, 2019 | 173 | 2019 |
| Convolutional neural networks performance comparison for handwritten Bengali numerals recognition MM Rahman, MS Islam, R Sassi, M Aktaruzzaman SN Applied Sciences 1 (12), 1660, 2019 | 52 | 2019 |
| Recognition bangla sign language using convolutional neural network MS Islalm, MM Rahman, MH Rahman, M Arifuzzaman, R Sassi, ... 2019 international conference on innovation and intelligence for informatics …, 2019 | 50 | 2019 |
| EyeNet: An improved eye states classification system using convolutional neural network MM Rahman, MS Islam, MKA Jannat, MH Rahman, M Arifuzzaman, ... 2020 22nd international conference on advanced communication technology …, 2020 | 21 | 2020 |
| A systematic survey of data augmentation of ECG signals for AI applications MM Rahman, MW Rivolta, F Badilini, R Sassi Sensors 23 (11), 5237, 2023 | 9 | 2023 |
| RATNet: A deep learning model for Bengali handwritten characters recognition MS Islam, MM Rahman, MH Rahman, MW Rivolta, M Aktaruzzaman Multimedia Tools and Applications 81 (8), 10631-10651, 2022 | 8 | 2022 |
| A deep learning-based multi-model ensemble method for eye state recognition from EEG MS Islalm, MM Rahman, MH Rahman, MR Hoque, AK Roonizi, ... 2021 IEEE 11th Annual Computing and Communication Workshop and Conference …, 2021 | 6 | 2021 |
| A decision support system for predicting settling velocity of spherical and non-spherical particles in Newtonian fluids S Rushd, M Rahman, M Arifuzzaman, M Aktaruzzaman Particulate Science and Technology 40 (5), 609-619, 2022 | 1 | 2022 |
| Predicting pressure losses in the water-assisted flow of unconventional crude with machine learning S Rushd, M Rahman, M Arifuzzaman, SA Ali, F Shalabi, M Aktaruzzaman Petroleum Science and Technology 39 (21-22), 926-943, 2021 | 1 | 2021 |
| Quantifying Uncertainty of a Deep Learning Model for Atrial Fibrillation Detection from ECG Signals MM Rahman, MW Rivolta, F Badilini, R Sassi 2023 Computing in Cardiology (CinC) 50, 1-4, 2023 | | 2023 |
Md AktaruzzamanProfessor, Dept. of Computer Science and Engineering, Islamic University, KushtiaVerified email at iu.ac.bd
