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Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation.

M. Yeung, L. Rundo, Y. Nan, E. Sala, C. Schönlieb, and G. Yang. J. Digit. Imaging, 36 (2): 739-752 (April 2023)

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Celia Yeung

Danny Yeung

Thomas Yeung

Kam Yeung

Donald Yeung

Other publications of authors with the same name

Calibrating the Dice loss to handle neural network overconfidence for biomedical image segmentation.M. Yeung, L. Rundo, Y. Nan, E. Sala, C. Schönlieb, and G. Yang. CoRR, (2021)Focal Attention Networks: optimising attention for biomedical image segmentation.M. Yeung, L. Rundo, E. Sala, C. Schönlieb, and G. Yang. CoRR, (2021)Incorporating Boundary Uncertainty into loss functions for biomedical image segmentation.M. Yeung, G. Yang, E. Sala, C. Schönlieb, and L. Rundo. CoRR, (2021)Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy.M. Yeung, E. Sala, C. Schönlieb, and L. Rundo. Comput. Biol. Medicine, (2021)Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation.M. Yeung, L. Rundo, Y. Nan, E. Sala, C. Schönlieb, and G. Yang. J. Digit. Imaging, 36 (2): 739-752 (April 2023)Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review.M. Roberts, D. Driggs, M. Thorpe, J. Gilbey, M. Yeung, S. Ursprung, A. Avilés-Rivero, C. Etmann, C. McCague, L. Beer and 5 other author(s). CoRR, (2020)Using advanced simulation to aid microlithography development.D. Cole, E. Barouch, E. Conrad, and M. Yeung. Proc. IEEE, 89 (8): 1194-1215 (2001)Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans.M. Roberts, D. Driggs, M. Thorpe, J. Gilbey, M. Yeung, S. Ursprung, A. Avilés-Rivero, C. Etmann, C. McCague, L. Beer and 6 other author(s). Nat. Mach. Intell., 3 (3): 199-217 (2021)From Astronomy to Histology: Adapting the FellWalker Algorithm to Deep Nuclear Instance Segmentation.M. Yeung, T. Watts, and G. Yang. MIUA, volume 13413 of Lecture Notes in Computer Science, page 547-561. Springer, (2022)Stain Consistency Learning: Handling Stain Variation for Automatic Digital Pathology Segmentation.M. Yeung, T. Watts, S. Tan, P. Ferreira, A. Scott, S. Nielles-Vallespin, and G. Yang. CoRR, (2023)

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Disambiguation of "Yeung, Michael"

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Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation.

Please choose a person to relate this publication to

Celia Yeung

Danny Yeung

Thomas Yeung

Kam Yeung

Donald Yeung

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Yeung, Michael"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation.

Please choose a person to relate this publication to

Celia Yeung

Danny Yeung

Thomas Yeung

Kam Yeung

Donald Yeung

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
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Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation.