Michael Yeung

According to our database, Michael Yeung authored at least 14 papers between 2001 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Noise-to-Notes: Diffusion-based Generation and Refinement for Automatic Drum Transcription.

Michael Yeung, Keisuke Toyama, Toya Teramoto, Shusuke Takahashi, Tamaki Kojima

CoRR, September, 2025

2024

VariFace: Fair and Diverse Synthetic Dataset Generation for Face Recognition.

Michael Yeung, Toya Teramoto, Songtao Wu, Tatsuo Fujiwara, Kenji Suzuki, Tamaki Kojima

CoRR, 2024

2023

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

Michael Yeung, Leonardo Rundo, Yang Nan, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang

J. Digit. Imaging, April, 2023

Stain Consistency Learning: Handling Stain Variation for Automatic Digital Pathology Segmentation.

Michael Yeung, Todd Watts, Sean YW Tan, Pedro F. Ferreira, Andrew D. Scott, Sonia Nielles-Vallespin, Guang Yang

CoRR, 2023

2022

Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation.

Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo

Comput. Medical Imaging Graph., 2022

From Astronomy to Histology: Adapting the FellWalker Algorithm to Deep Nuclear Instance Segmentation.

Michael Yeung, Todd Watts, Guang Yang

Proceedings of the Medical Image Understanding and Analysis - 26th Annual Conference, 2022

Focal Attention Networks: Optimising Attention for Biomedical Image Segmentation.

Michael Yeung, Leonardo Rundo, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang

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.

Michael Roberts, Derek Driggs, Matthew Thorpe, Julian D. Gilbey, Michael Yeung, Stephan Ursprung, Angelica I. Avilés-Rivero, Christian Etmann, Cathal McCague, Lucian Beer, Jonathan R. Weir-McCall, Zhongzhao Teng, Effrossyni Gkrania-Klotsas, James H. F. Rudd, Evis Sala, Carola-Bibiane Schönlieb

Nat. Mach. Intell., 2021

Incorporating Boundary Uncertainty into loss functions for biomedical image segmentation.

Michael Yeung, Guang Yang, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo

CoRR, 2021

Advances in Artificial Intelligence to Reduce Polyp Miss Rates during Colonoscopy.

Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo

CoRR, 2021

A Mixed Focal Loss Function for Handling Class Imbalanced Medical Image Segmentation.

Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo

CoRR, 2021

Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy.

Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo

Comput. Biol. Medicine, 2021

2020

Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review.

Michael Roberts, Derek Driggs, Matthew Thorpe, Julian D. Gilbey, Michael Yeung, Stephan Ursprung, Angelica I. Avilés-Rivero, Christian Etmann, Cathal McCague, Lucian Beer, Jonathan R. Weir-McCall, Zhongzhao Teng, James H. F. Rudd, Evis Sala, Carola-Bibiane Schönlieb

CoRR, 2020

2001

Using advanced simulation to aid microlithography development.

Daniel C. Cole, Eytan Barouch, Edward W. Conrad, Michael Yeung

Proc. IEEE, 2001