This repository implements a variety of fully convolutional neural networks for semantic segmentation using Keras. Fully convolutional networks make classification predictions at every pixel in an image instead of giving a single class output. This means as output you get both a segmentation map and a classification distribution. This repository has a simple implementation of the original fully convolutional network (fcn) and the network proposed in the paper Multi-Scale Context Aggregation by Dilated Convolutions (dilation8). This clean implementation serves as a great starting place for fully convolutional models and was created as part of a research project on coral reef image data (the displayed image is a segmentation map of a coral reef).