[Solved] How to tackle the Massachusetts roads dataset using CNN in Keras?

Question

This problems is a binary segmentation problem. In a sense you learn a mapping from satellite images and predict for each pixel, iff this pixel is part of the road. A simple algorithm to do this would be to check if the pixel color is part of some range.

A CNN naturally will learn you a more complicated function based on the local neighborhood of said pixel. One repo to get you started should be this one: https://github.com/jocicmarko/ultrasound-nerve-segmentation. Therein they use a similar algorithm to segment ultrasound images using CNNs. You just have to use 3 input channels instead of 1 and everything else should be quite similar.

Accepted Answer

This problems is a binary segmentation problem. In a sense you learn a mapping from satellite images and predict for each pixel, iff this pixel is part of the road. A simple algorithm to do this would be to check if the pixel color is part of some range.

A CNN naturally will learn you a more complicated function based on the local neighborhood of said pixel. One repo to get you started should be this one: https://github.com/jocicmarko/ultrasound-nerve-segmentation. Therein they use a similar algorithm to segment ultrasound images using CNNs. You just have to use 3 input channels instead of 1 and everything else should be quite similar.