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ORCIDGrace Y. Wang
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- affiliation (PhD): Auckland University of Technology, Department of Psychology and Neuroscience, New Zealand
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Journal Articles
- 2023
[j8]Maryam Doborjeh
, Xiaoxu Liu, Zohreh Gholami Doborjeh, Yuanyuan Shen, Grant Searchfield, Philip J. Sanders, Grace Y. Wang, Alexander Sumich, Wei Qi Yan:
Prediction of Tinnitus Treatment Outcomes Based on EEG Sensors and TFI Score Using Deep Learning. Sensors 23(2): 902 (2023)- 2021
- [j7]Mahima Milinda Alwis Weerasinghe, Josafath Israel Espinosa Ramos, Grace Y. Wang, Dave Parry:
Incorporating Structural Plasticity Approaches in Spiking Neural Networks for EEG Modelling. IEEE Access 9: 117338-117348 (2021) - [j6]Maryam Doborjeh, Zohreh Gholami Doborjeh, Nikola K. Kasabov, Molood Barati, Grace Y. Wang:
Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network. Sensors 21(14): 4900 (2021) - 2020
- [j5]Terry Gao, Grace Ying Wang:
Brain Signal Classification Based on Deep CNN. Int. J. Secur. Priv. Pervasive Comput. 12(2): 17-29 (2020) - [j4]Zohreh Gholami Doborjeh, Maryam Doborjeh, Mark Crook-Rumsey, Tamasin Taylor, Grace Y. Wang, David Moreau, Christian U. Krägeloh, Wendy Wrapson, Richard J. Siegert, Nikola K. Kasabov, Grant Searchfield, Alexander Sumich:
Interpretability of Spatiotemporal Dynamics of the Brain Processes Followed by Mindfulness Intervention in a Brain-Inspired Spiking Neural Network Architecture. Sensors 20(24): 7354 (2020) - 2016
- [j3]Nikola K. Kasabov, Nathan Matthew Scott, Enmei Tu, Stefan Marks, Neelava Sengupta, Elisa Capecci, Muhaini Othman, Maryam Gholami Doborjeh, Norhanifah Murli, Reggio N. Hartono, Josafath Israel Espinosa Ramos, Lei Zhou, Fahad Bashir Alvi, Grace Y. Wang, Denise Taylor, Valery Feigin, Sergei Gulyaev, Mahmoud S. Mahmoud, Zeng-Guang Hou, Jie Yang:
Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications. Neural Networks 78: 1-14 (2016) - [j2]Maryam Gholami Doborjeh, Grace Y. Wang, Nikola K. Kasabov, Robert Kydd, Bruce Russell:
A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects. IEEE Trans. Biomed. Eng. 63(9): 1830-1841 (2016) - 2015
- [j1]Elisa Capecci, Nikola K. Kasabov, Grace Y. Wang:
Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment. Neural Networks 68: 62-77 (2015)
Conference and Workshop Papers
- 2024
- [c2]Christopher Wigell, Xiaohui Tao, Lin Li, Grace Y. Wang, Ji Zhang, Yuan Sun:
Sentiment Analysis for Detection of Depressive Users on Social Networks. BESC 2024: 1-7 - 2019
- [c1]Dhvani Shah, Grace Y. Wang, Maryam Doborjeh, Zohreh Gholami Doborjeh, Nikola K. Kasabov:
Deep Learning of EEG Data in the NeuCube Brain-Inspired Spiking Neural Network Architecture for a Better Understanding of Depression. ICONIP (3) 2019: 195-206
Informal and Other Publications
- 2022
- [i1]Mahima Milinda Alwis Weerasinghe, David Parry, Grace Y. Wang, Jacqueline Whalley:
Ensemble plasticity and network adaptability in SNNs. CoRR abs/2203.07039 (2022)
Coauthor Index
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