There are 4 repositories under fully-convolutional-networks topic.
Semantic Segmentation Architectures Implemented in PyTorch
A Keras port of Single Shot MultiBox Detector
PyTorch for Semantic Segmentation
Simple PyTorch implementations of U-Net/FullyConvNet (FCN) for image segmentation
A PyTorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
🚀 😏 Near Real Time CPU Face detection using deep learning
A Deep Learning library for EEG Tasks (Signals) Classification, based on TensorFlow.
🚘 Easiest Fully Convolutional Networks
Source code for the MICCAI 2016 Paper "Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional NeuralNetworks and 3D Conditional Random Fields"
liver segmentation using deep learning
PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks
A Single Shot MultiBox Detector in TensorFlow
U-Time: A Fully Convolutional Network for Time Series Segmentation
Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.
Tensorflow implementation : U-net and FCN with global convolution
Convolutional Neural Networks for Cardiac Segmentation
Semantically segment the road in the given image.
Keras implementation of paper by the same name
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images
Semantic Image Segmentation using a Fully Convolutional Neural Network in TensorFlow
The first fully convolutional metric learning for geometric/semantic image correspondences.
Deep and Machine Learning for Microscopy
[ICCV 2015] Framework for optimizing CNNs with linear constraints for Semantic Segmentation
Training a deep FCN network in PyTorch to route circuit layouts
A TensorFlow Implementation of Fully Convolutional Networks
A Keras-Tensorflow Fully Convolutional Network that performs image segmentation on faces
Segmentation of prostate from MRI scans
Building, training and deploying a fully convolutional neural network in TensorFlow
Label-Pixels is a tool for semantic segmentation of remote sensing images using fully convolutional networks (FCNs), designed for extracting the road network from remote sensing imagery and it can be used in other applications applications to label every pixel in the image ( Semantic segmentation).
[SAIN'18] [Caffe] A dilated version of FCN with Stride 2 for Efficient Semantic Segmentation
Actionness Estimation Using Hybrid Fully Convolutional Networks
This is a PyTorch implementation of the the Paper by Simo-Sera et.al. on Cleaning Rough Sketches using Fully Convolutional Neural Networks.
NCI-ISBI 2013 Challenge - Automated Segmentation of Prostate Structures