Michael Yeung
Orcid: 0000-0001-8700-9144
According to our database1,
Michael Yeung
authored at least 12 papers
between 2001 and 2023.
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Bibliography
2023
Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation.
J. Digit. Imaging, April, 2023
Stain Consistency Learning: Handling Stain Variation for Automatic Digital Pathology Segmentation.
CoRR, 2023
2022
Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation.
Comput. Medical Imaging Graph., 2022
From Astronomy to Histology: Adapting the FellWalker Algorithm to Deep Nuclear Instance Segmentation.
Proceedings of the Medical Image Understanding and Analysis - 26th Annual Conference, 2022
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022
2021
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans.
Nat. Mach. Intell., 2021
Incorporating Boundary Uncertainty into loss functions for biomedical image segmentation.
CoRR, 2021
CoRR, 2021
A Mixed Focal Loss Function for Handling Class Imbalanced Medical Image Segmentation.
CoRR, 2021
Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy.
Comput. Biol. Medicine, 2021
2020
Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review.
CoRR, 2020
2001