Michael Yeung - RankMe

16 papers Journal 14Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Noise-to-Notes: Diffusion-based Generation and Refinement for Automatic Drum Transcription. CoRR Michael Yeung, Keisuke Toyama, Toya Teramoto, Shusuke Takahashi, Tamaki Kojima
2024	J	`jnl`	VariFace: Fair and Diverse Synthetic Dataset Generation for Face Recognition. CoRR Michael Yeung, Toya Teramoto, Songtao Wu, Tatsuo Fujiwara, Kenji Suzuki, Tamaki Kojima
2023	J	`jnl`	Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation. J. Digit. Imaging Michael Yeung, Leonardo Rundo, Yang Nan, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang
2023	J	`jnl`	Stain Consistency Learning: Handling Stain Variation for Automatic Digital Pathology Segmentation. CoRR Michael Yeung, Todd Watts, Sean YW Tan, Pedro F. Ferreira, Andrew D. Scott, Sonia Nielles-Vallespin, Guang Yang
2022	—	`conf`	Focal Attention Networks: Optimising Attention for Biomedical Image Segmentation. ISBI Michael Yeung, Leonardo Rundo, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang
2022	—	`conf`	From Astronomy to Histology: Adapting the FellWalker Algorithm to Deep Nuclear Instance Segmentation. MIUA Michael Yeung, Todd Watts, Guang Yang
2022	J	`jnl`	Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation. Comput. Medical Imaging Graph. Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo
2021	J	`jnl`	A Mixed Focal Loss Function for Handling Class Imbalanced Medical Image Segmentation. CoRR Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo
2021	J	`jnl`	Advances in Artificial Intelligence to Reduce Polyp Miss Rates during Colonoscopy. CoRR Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo
2021	J	`jnl`	Calibrating the Dice loss to handle neural network overconfidence for biomedical image segmentation. CoRR Michael Yeung, Leonardo Rundo, Yang Nan, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang
2021	J	`jnl`	Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans. Nat. Mach. Intell. 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
2021	J	`jnl`	Focal Attention Networks: optimising attention for biomedical image segmentation. CoRR Michael Yeung, Leonardo Rundo, Evis Sala, Carola-Bibiane Schönlieb, Guang Yang
2021	J	`jnl`	Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy. Comput. Biol. Medicine Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo
2021	J	`jnl`	Incorporating Boundary Uncertainty into loss functions for biomedical image segmentation. CoRR Michael Yeung, Guang Yang, Evis Sala, Carola-Bibiane Schönlieb, Leonardo Rundo
2020	J	`jnl`	Machine learning for COVID-19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review. CoRR 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
2001	J	`jnl`	Using advanced simulation to aid microlithography development. Proc. IEEE Daniel C. Cole, Eytan Barouch, Edward W. Conrad, Michael Yeung