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Detecting hip fractures with radiologist-level performance using deep neural networks
William Gale, Luke Oakden-Rayner, Gustavo Carneiro +2
We developed an automated deep learning system to detect hip fractures from frontal pelvic x-rays, an important and common radiological task. Our system was trained on a decade of…
A Bayesian Data Augmentation Approach for Learning Deep Models
Toan Tran, Trung Pham, Gustavo Carneiro +2
Data augmentation is an essential part of the training process applied to deep learning models. The motivation is that a robust training process for deep learning models depends on…
Domain-adversarial neural networks to address the appearance variability of histopathology images
Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof +2
Preparing and scanning histopathology slides consists of several steps, each with a multitude of parameters. The parameters can vary between pathology labs and within the same lab…
Smart Mining for Deep Metric Learning
Ben Harwood, Vijay Kumar B G, Gustavo Carneiro +2
To solve deep metric learning problems and producing feature embeddings, current methodologies will commonly use a triplet model to minimise the relative distance between samples f…