Originally, this Project was based on the twelfth task of the Udacity Self-Driving Car Nanodegree program. The main goal of the project is to train an artificial neural network for semantic segmentation of a video from a front-facing camera on a car in order to mark road pixels with Tensorflow (using the KITTI dataset).

Additianally, multiclass semantic segmentation for the Cityscapes was added.

Contents:

1. Neural network for multiclass image segmentation

The full project code is available on my Github

Project posts

21 Sep 2017

Neural network for multiclass image segmentation

VGG16-based fully convolutional networks for semantic segmentation of images on Cityscapes

3 mins read