《深度学习与计算机视觉》配套代码
-
Updated
Nov 30, 2020 - Python
《深度学习与计算机视觉》配套代码
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.
Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai
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.
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
U-Net Biomedical Image Segmentation
Official repo for Medical Image Segmentation Review: The Success of U-Net
Python library for designing and training your own Diffusion Models with PyTorch.
Implementation of a U-net complete with efficient attention as well as the latest research findings
Deep Learning sample programs using PyTorch in C++
Official implementation of DoubleU-Net for Semantic Image Segmentation in TensorFlow & Pytorch (Nominated for Best Paper Award (IEEE CBMS))
Code for "Quantized Densely Connected U-Nets for Efficient Landmark Localization" (ECCV 2018) and "CU-Net: Coupled U-Nets" (BMVC 2018 oral)
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.
Attention-Guided Version of 2D UNet for Automatic Brain Tumor Segmentation
A Pytorch implementation of Stylegan2 with UNet Discriminator
Add a description, image, and links to the u-net topic page so that developers can more easily learn about it.
To associate your repository with the u-net topic, visit your repo's landing page and select "manage topics."