1 citations · 1 across the 2 of their papers we have counts for
5 papers
Temporal Cluster Assignment for Efficient Real-Time Video Segmentation
Ka-Wai Yung, Felix J. S. Bragman, Jialang Xu +3
Vision Transformers have substantially advanced the capabilities of segmentation models across both image and video domains. Among them, the Swin Transformer stands out for its abi…
A spatio-temporal network for video semantic segmentation in surgical videos
Maria Grammatikopoulou, Ricardo Sanchez-Matilla, Felix Bragman +5
Semantic segmentation in surgical videos has applications in intra-operative guidance, post-operative analytics and surgical education. Segmentation models need to provide accurate…
Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels
Felix J. S. Bragman, Ryutaro Tanno, Sebastien Ourselin +2
The performance of multi-task learning in Convolutional Neural Networks (CNNs) hinges on the design of feature sharing between tasks within the architecture. The number of possible…
Towards safe deep learning: accurately quantifying biomarker uncertainty in neural network predictions
Zach Eaton-Rosen, Felix Bragman, Sotirios Bisdas +2
Automated medical image segmentation, specifically using deep learning, has shown outstanding performance in semantic segmentation tasks. However, these methods rarely quantify the…
Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning
Felix J. S. Bragman, Ryutaro Tanno, Zach Eaton-Rosen +6
Multi-task neural network architectures provide a mechanism that jointly integrates information from distinct sources. It is ideal in the context of MR-only radiotherapy planning a…