There are 4 repositories under u-net topic.
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
Real-Time Semantic Segmentation in Mobile device
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
Winning solution for the Kaggle TGS Salt Identification Challenge.
Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks
Official Implementation of the paper "A U-Net Based Discriminator for Generative Adversarial Networks" (CVPR 2020)
Using a U-Net for image segmentation, blending predicted patches smoothly is a must to please the human eye.
Code for "Quantized Densely Connected U-Nets for Efficient Landmark Localization" (ECCV 2018) and "CU-Net: Coupled U-Nets" (BMVC 2018 oral)
Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
U-Net Biomedical Image Segmentation
Manage your machine learning experiments with trixi - modular, reproducible, high fashion. An experiment infrastructure optimized for PyTorch, but flexible enough to work for your framework and your tastes.
Deep Learning sample programs using PyTorch in C++
A Pytorch implementation of Stylegan2 with UNet Discriminator
DoubleU-Net for Semantic Image Segmentation in TensorFlow Keras (Nominated for Best Paper Award (IEEE CBMS))
RObust document image BINarization
PyTorch Implementation of Stacked U-Nets (SUNets)
Dstl Satellite Imagery Feature Detection
A deep learning based approach for brain tumor MRI segmentation.
Attention-Guided Version of 2D UNet for Automatic Brain Tumor Segmentation
Tensorflow implementation : U-net and FCN with global convolution
DATA-SCIENCE-BOWL-2018 Find the nuclei in divergent images to advance medical discovery
Segmentation of ID Cards using Semantic Segmentation
Edge-aware U-Net with CRF-RNN layer for Medical Image Segmentation
Robust Chest CT Image Segmentation of COVID-19 Lung Infection based on limited data
CNNs for semantic segmentation using Keras library
A PyTorch implementation of image steganography utilizing deep convolutional neural networks
Autonomous navigation for blind people
Segmentation for vertebra in MR images
Road Extraction based on U-Net architecture (CVPR2018 DeepGlobe Challenge submission)
Detect location and draw boundary of nuclei from microscopic images
pytorch implementation of paper https://www.frontiersin.org/articles/10.3389/fcomp.2020.00035/full
Pre-trained model, code, and materials from the paper "Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation" (MICCAI 2019).
#BRATS2015 #BRATS2018 #deep learning #fully automatic brain tumor segmentation #U-net # tensorflow #Keras