Michael Z. Liu
Orcid: 0000-0002-9609-4544
According to our database1,
Michael Z. Liu
authored at least 16 papers
between 2018 and 2022.
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Bibliography
2022
IEEE Trans. Smart Grid, 2022
Comput. Biol. Medicine, 2022
Residential PV Hosting Capacity, Voltage Unbalance, and Power Rebalancing: An Australian Case Study.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Conference Europe, 2022
2021
Ensuring Distribution Network Integrity Using Dynamic Operating Limits for Prosumers.
IEEE Trans. Smart Grid, 2021
IEEE Trans. Smart Grid, 2021
3D Isotropic Super-resolution Prostate MRI Using Generative Adversarial Networks and Unpaired Multiplane Slices.
J. Digit. Imaging, 2021
2020
Optimal Power Flow for Active Distribution Networks: Advanced Formulations, Practical Considerations and Laboratory Demonstration.
PhD thesis, 2020
IEEE Trans. Smart Grid, 2020
Channel width optimized neural networks for liver and vessel segmentation in liver iron quantification.
Comput. Biol. Medicine, 2020
Operating Envelopes for Prosumers in LV Networks: A Weighted Proportional Fairness Approach.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe, 2020
On the Role of Pre-Curtailed Residential PV for Primary Frequency Response Considering Distribution Network Constraints.
Proceedings of the IEEE PES Innovative Smart Grid Technologies Europe, 2020
2019
Convolutional Neural Networks for the Detection and Measurement of Cerebral Aneurysms on Magnetic Resonance Angiography.
J. Digit. Imaging, 2019
Predicting Breast Cancer Molecular Subtype with MRI Dataset Utilizing Convolutional Neural Network Algorithm.
J. Digit. Imaging, 2019
Fully Automated Convolutional Neural Network Method for Quantification of Breast MRI Fibroglandular Tissue and Background Parenchymal Enhancement.
J. Digit. Imaging, 2019
Prior to Initiation of Chemotherapy, Can We Predict Breast Tumor Response? Deep Learning Convolutional Neural Networks Approach Using a Breast MRI Tumor Dataset.
J. Digit. Imaging, 2019
2018
Axillary Lymph Node Evaluation Utilizing Convolutional Neural Networks Using MRI Dataset.
J. Digit. Imaging, 2018