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Rebecca Stone's Projects

baypolypgen-benchmark icon baypolypgen-benchmark

De-biasing (out-of-distribution mitigation) methods based on Bayesian epistemic uncertainties tested on Polyp dataset.

baysharpen-debias icon baysharpen-debias

Code for paper "Implicit Visual Bias Mitigation by Posterior Estimate Sharpening of a Bayesian Neural Network"

bcsp-expert icon bcsp-expert

Project studying the differences between difficult diagnoses, particularly epithelial misplacement vs carcinoma.

blue-elephants icon blue-elephants

Sample Flask app to be deployed for COMP2011 Web Application Development module Autumn2018.

bootstrap-calendar icon bootstrap-calendar

Full view calendar with year, month, week and day views based on templates with Twitter Bootstrap.

csgmcmc icon csgmcmc

Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning

extremeearth-polar icon extremeearth-polar

ExtremeEarth Polar Classification - prototype model/testing for ULeeds CDT event, School of Earth and Environment

flickr8k-custom icon flickr8k-custom

Flickr8k dataset for COMP5623M but with labeled test/train set splits.

fwat icon fwat

A Fast Whole-slide image Annotation Tool (FWAT) for conducting painless studies requiring annotations on whole-slide images.

imagepy-toolkit icon imagepy-toolkit

Various helpful functions for simplifying Python image manipulation

isic-subset icon isic-subset

Subset of the ISIC Archive for research purposes only.

letterbox-it icon letterbox-it

A web app to track distribution of materials by letterbox.

nucleisegmentation icon nucleisegmentation

This is the source code for training and testing a three class CNN for nuclei segmentation using Torch

polar-patch icon polar-patch

Set of approx 10,000 image patches from ExtremeEarth Polar Use Case Training Data (https://zenodo.org/record/3695276#.YBfpIJP7RhG) with training labels.

py-wsi icon py-wsi

Python package for dealing with whole slide images (.svs) for machine learning, particularly for fast prototyping. Includes patch sampling and storing using OpenSlide. Patches may be stored in LMDB, HDF5 files, or to disk. It is highly recommended to fork and download this repository so that personal customisations can be made for your work.

pytorch-bayesiancnn icon pytorch-bayesiancnn

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

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