Ashraf, H., Waris, A., Gilani, S. O., Shafiq, U., Iqbal, J., Kamavuako, E. N., Berrouche, Y., Bruls, O., Boutaayamou, M., & Niazi, I. K. (23 January 2024). Optimizing the performance of convolutional neural network for enhanced gesture recognition using sEMG. Scientific Reports, 14 (1), 2020. doi:10.1038/s41598-024-52405-9 |
Ashraf, H., Shafiq, U., Sajjad, Q., Waris, A., Gilani, O., Boutaayamou, M., & Brüls, O. (April 2023). Variational mode decomposition for surface and intramuscular EMG signal denoising. Biomedical Signal Processing and Control, 82, 104560. doi:10.1016/j.bspc.2022.104560 |
Ashraf, H., Brüls, O., Schwartz, C., & Boutaayamou, M. (2023). Comparison of Machine Learning Algorithms for Human Activity Recognition. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies. Lisbon, Portugal: SciTePress. doi:10.5220/0011631500003414 |
Ashraf, H., Waris, A., Ghafoor, M. F., Gilani, S. O., & Niazi, I. K. (December 2022). Melanoma segmentation using deep learning with test-time augmentations and conditional random fields. Scientific Reports, 12 (1). doi:10.1038/s41598-022-07885-y |
Ashraf, H., Boutaayamou, M., Bruls, O., & Schwartz, C. (11 October 2022). Human Activity Recognition for the Assessment of Daily-life Activities Using Machine Learning [Poster presentation]. 20th National Day of Biomedical Engineering, Brussels, Belgium. |
Ashraf, H., Waris, A., Gilani, S. O., Tariq, M. U., & Alquhayz, H. (2021). Threshold parameters selection for empirical mode decomposition-based emg signal denoising. Intelligent Automation and Soft Computing, 27 (3), 799 - 815. doi:10.32604/IASC.2021.014765 |
Asif, A. R., Waris, A., Gilani, S. O., Jamil, M., Ashraf, H., Shafique, M., & Niazi, I. K. (02 March 2020). Performance evaluation of convolutional neural network for hand gesture recognition using EMG. Sensors (Switzerland), 20 (6), 1642. doi:10.3390/s20061642 |
Ashraf, H., Waris, A., Jamil, M., Gilani, S. O., Niazi, I. K., Kamavuako, E. N., & Gilani, S. H. N. (2020). Determination of Optimum Segmentation Schemes for Pattern Recognition-Based Myoelectric Control: A Multi-Dataset Investigation. IEEE Access, 8, 90862 - 90877. doi:10.1109/ACCESS.2020.2994829 |