5 papers
PLESS: Pseudo-Label Enhancement with Spreading Scribbles for Weakly Supervised Segmentation
Yeva Gabrielyan, Varduhi Yeghiazaryan, Irina Voiculescu
Weakly supervised learning with scribble annotations uses sparse user-drawn strokes to indicate segmentation labels on a small subset of pixels. This annotation reduces the cost of…
Reg4Pru: Regularisation Through Random Token Routing for Token Pruning
Julian Wyatt, Ronald Clark, Irina Voiculescu
Transformers are widely adopted in modern vision models due to their strong ability to scale with dataset size and generalisability. However, this comes with a major drawback: comp…
MUPAX: Multidimensional Problem Agnostic eXplainable AI
Vincenzo Dentamaro, Felice Franchini, Giuseppe Pirlo +1
Robust XAI techniques should ideally be simultaneously deterministic, model agnostic, and guaranteed to converge. We propose MULTIDIMENSIONAL PROBLEM AGNOSTIC EXPLAINABLE AI (MUPAX…
Entropy Bootstrapping for Weakly Supervised Nuclei Detection
James Willoughby, Irina Voiculescu
Microscopy structure segmentation, such as detecting cells or nuclei, generally requires a human to draw a ground truth contour around each instance. Weakly supervised approaches (…
Optimising for the Unknown: Domain Alignment for Cephalometric Landmark Detection
Julian Wyatt, Irina Voiculescu
Cephalometric Landmark Detection is the process of identifying key areas for cephalometry. Each landmark is a single GT point labelled by a clinician. A machine learning model pred…