| Population graph-based multi-model ensemble method for diagnosing autism spectrum disorder Z Rakhimberdina, X Liu, T Murata Sensors 20 (21), 6001, 2020 | 35 | 2020 |
| Natural image reconstruction from fmri using deep learning: A survey Z Rakhimberdina, Q Jodelet, X Liu, T Murata Frontiers in neuroscience 15, 795488, 2021 | 27 | 2021 |
| Linear graph convolutional model for diagnosing brain disorders Z Rakhimberdina, T Murata Complex Networks and Their Applications VIII: Volume 2 Proceedings of the …, 2020 | 26 | 2020 |
| Improving MOOC quality using learning analytics and tools JS Cross, N Keerativoranan, MKJ Carlon, YH Tan, Z Rakhimberdina, ... 2019 ieee learning with moocs (lwmoocs), 174-179, 2019 | 14 | 2019 |
| Strengthening Robustness Under Adversarial Attacks Using Brain Visual Codes Z Rakhimberdina, X Liu, T Murata IEEE Access 10, 96149-96158, 2022 | 1 | 2022 |
| Improving automated detection of autism spectrum disorder with deep learning based on resting-state and task-based fMRI data Z RAKHIMBERDINA, T MURATA (No Title), 2023 | | 2023 |
| Meritorious Service Award JS Cross, N Keerativoranan, MKJ Carlon, YH Tan, Z Rakhimberdina, ... | | |
