What to use for Semantic Segmentation

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Hello, just to briefly introduce myself, I am just starting to work with deep learning and I don't really know much about it. I have a task that I want to complete and I would very much appreciate to be given some sort of a direction about what should I start to look at and learn about.
My task is to perform semantic segmentation on images like the following:
I have about 1500 similar images as a training set, which are not pixel label classified. The task is the be able to get information about where on a new image are there structures like the ones marked with green.
Should I look at some premade neural network architectures for semantic segmentation, or would I need something custom. Also, do I have to create pixel labels for the images by hand to train a network, or is there a more automatic approach?

Accepted Answer

Sebastian Castro
Sebastian Castro on 7 Nov 2018
Edited: Sebastian Castro on 7 Nov 2018
You can start with premade neural network architectures. The following example does this with the VGG-16 architecture:
As far as labeling the pixel data, check this out:
- Sebastian

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