Illustration taken from the U-Net paper I recently read an interesting paper titled “U-Net: Convolutional Networks for Biomedical Image Segmentation” by Olaf Ronneberger, Philipp Fischer, and Thomas Brox which describes how to handle challenges in image segmentation in biomedical settings which I summarize in this blog post. Challenges for medical image segmentation A typical task when confronted with medical images is segmentation. That refers to finding out interesting objects in an image.
Deep Q Learning Today, I want to show you how you can use deep Q learning to let an agent learn how to play a game. Deep Q learning is a method which was introduced by DeepMind in their 2015 Nature paper (pdf) to play Atari video games by just observing the pixels of the game. To make it a bit simpler for the case of this blog post, we will use a slightly easier game which is to balance a polestick on a paddle.
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