Previously, I discussed training a neural net to clean up images. I’m pleased to say that, using more sophisticated techniques, I’ve since achieved much better results. My latest approach is a four layer convolutional network. Sadly, the convolution throws away the sides of the images, so we get a black margin. In any case, compare the results:
Now, all these results are based on images from the same source, Dror Bar-Natan’s Pensieve. Thus, even though I’ve used separate training and test images, they aren’t really independent. It would be much more interesting to look at how well it does when seeing a very different image… The following is Richard Feynman’s blackboard when he died.
(I find Caltech’s copyrighting an image of dead persons’s blackboard and coating most of the images with “Caltech Archive”, to be in really poor taste and rude.)
The only preprocessing was scaling the image by a factor of two so that things were of similar scale.
I’m trying to write a super easy to use neural net library. We’ll see where this goes.