40 citations · 47 across the 6 of their papers we have counts for
3 papers · 1 filter
Many tasks make light work: Learning to localise medical anomalies from multiple synthetic tasks
Matthew Baugh, Jeremy Tan, Johanna P. Müller +3
There is a growing interest in single-class modelling and out-of-distribution detection as fully supervised machine learning models cannot reliably identify classes not included in…
Zero-Shot Anomaly Detection with Pre-trained Segmentation Models
Matthew Baugh, James Batten, Johanna P. Müller +1
This technical report outlines our submission to the zero-shot track of the Visual Anomaly and Novelty Detection (VAND) 2023 Challenge. Building on the performance of the WINCLIP f…
Image To Tree with Recursive Prompting
James Batten, Matthew Sinclair, Ben Glocker +1
Extracting complex structures from grid-based data is a common key step in automated medical image analysis. The conventional solution to recovering tree-structured geometries typi…