Fc Densenet
Fully Convolutional DenseNets for semantic segmentation.
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Fc Densenet | 480 | 2 years ago | 22 | Python | ||||||
| Fully Convolutional DenseNets for semantic segmentation. | ||||||||||
| Livianet | 133 | 4 years ago | 6 | mit | Python | |||||
| This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study" | ||||||||||
| Reseg | 120 | 7 years ago | gpl-3.0 | Python | ||||||
| A Recurrent Neural Network for Object Segmentation | ||||||||||
| Adaptationseg | 116 | 3 years ago | 11 | Python | ||||||
| Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes, ICCV 2017 | ||||||||||
| Hyperdensenet | 106 | 4 years ago | 2 | mit | Python | |||||
| This repository contains the code of HyperDenseNet, a hyper-densely connected CNN to segment medical images in multi-modal image scenarios. | ||||||||||
| Promise12_segmentation | 66 | 6 years ago | 4 | Python | ||||||
| Codes that I have written to complete promise12 prostate segmentation competition. | ||||||||||
| Semidensenet | 48 | 6 years ago | 3 | mit | Python | |||||
| Repository containing the code of one of the networks that we employed in the iSEG Grand MICCAI Challenge 2017, infant brain segmentation. | ||||||||||
| Nicmslesions | 34 | 2 years ago | 5 | gpl-3.0 | C++ | |||||
| Easy multiple sclerosis white matter lesion segmentation using convolutional deep neural networks. | ||||||||||
| Road Segmentation | 31 | 7 years ago | 2 | Jupyter Notebook | ||||||
| Satellite image segmentation (extraction of roads from satellite images) through convolutional neural networks (CNNs). | ||||||||||
| Hippodeep | 14 | 4 years ago | 1 | mit | Python | |||||
| Brain Hippocampus Segmentation | ||||||||||
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