Pinned Repositories
3DUnetCNN
Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation
ADNet
Code for the paper "Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels".
extracting-tiles-in-multilevel-gigapixel-images
gekko
A bitcoin trading bot written in node - https://gekko.wizb.it/
hitgan
The masters thesis carried out by orjan and carl
ISLES2018
Code and models for the paper ISLES Challenge: U-shaped Convolution Neural Network with Dilated Convolution for 3D Stroke Lesion Segmentation
keract
Activation Maps (Layers Outputs) and Gradients in Keras.
multiscale-tissue-segmentation-for-urothelial-carcinoma
opencv
Open Source Computer Vision Library
Self-supervised-Fewshot-Medical-Image-Segmentation
[ECCV'20] Self-supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation (code&data-processing pipeline)
tom501's Repositories
tom501/3DUnetCNN
Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation
tom501/ADNet
Code for the paper "Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels".
tom501/extracting-tiles-in-multilevel-gigapixel-images
tom501/gekko
A bitcoin trading bot written in node - https://gekko.wizb.it/
tom501/hitgan
The masters thesis carried out by orjan and carl
tom501/ISLES2018
Code and models for the paper ISLES Challenge: U-shaped Convolution Neural Network with Dilated Convolution for 3D Stroke Lesion Segmentation
tom501/keract
Activation Maps (Layers Outputs) and Gradients in Keras.
tom501/multiscale-tissue-segmentation-for-urothelial-carcinoma
tom501/opencv
Open Source Computer Vision Library
tom501/Self-supervised-Fewshot-Medical-Image-Segmentation
[ECCV'20] Self-supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation (code&data-processing pipeline)
tom501/thesis-template
LaTeX template for PhD, Master, or Bachelor thesis at University of Stavanger
tom501/Thresholding-CTP
tom501/uis-dat630-fall2017
UiS DAT630 Web Search and Data Mining course, fall 2017
tom501/unet
Keras implementation of a 2D/3D U-Net with Additive Attention, Inception, and Recurrence functions provided