8 citations · 27 across the 19 of their papers we have counts for
13 papers · 1 filter
SharkTrack: an accurate, generalisable software for streamlining shark and ray underwater video analysis
Filippo Varini, Joel H. Gayford, Jeremy Jenrette +11
Elasmobranchs (shark sand rays) represent a critical component of marine ecosystems. Yet, they are experiencing global population declines and effective monitoring of populations i…
Mitigating attribute amplification in counterfactual image generation
Tian Xia, Mélanie Roschewitz, Fabio De Sousa Ribeiro +2
Causal generative modelling is gaining interest in medical imaging due to its ability to answer interventional and counterfactual queries. Most work focuses on generating counterfa…
Robust semi-supervised segmentation with timestep ensembling diffusion models
Margherita Rosnati, Melanie Roschewitz, Ben Glocker
Medical image segmentation is a challenging task, made more difficult by many datasets' limited size and annotations. Denoising diffusion probabilistic models (DDPM) have recently…
Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation
Zeju Li, Konstantinos Kamnitsas, Qi Dou +2
This paper presents an effective and general data augmentation framework for medical image segmentation. We adopt a computationally efficient and data-efficient gradient-based meta…
Measuring axiomatic soundness of counterfactual image models
Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski +2
We present a general framework for evaluating image counterfactuals. The power and flexibility of deep generative models make them valuable tools for learning mechanisms in structu…
Paced-Curriculum Distillation with Prediction and Label Uncertainty for Image Segmentation
Mobarakol Islam, Lalithkumar Seenivasan, S. P. Sharan +4
Purpose: In curriculum learning, the idea is to train on easier samples first and gradually increase the difficulty, while in self-paced learning, a pacing function defines the spe…