Just a quick idea. I thought I use pyevolve ( genetic algorithm – python module ) to see if I could generate an image from a machine learning network. I thought I have a classifier which I would get some real valued number from (going to strip the binary function in the end). This indication is going into the genetic algorithm as a score. Then the algorthm generates new guesses which will be selected from.
Its my project for this time.
Have not got around to testing. But I found out something interesting. Using the handwritten digits I manage to get much better accuracy for the digit recognition from adding noise digits and classifying them as their own special number.
Thats is. I added 180 numpy.random.rand(8,8) matrices to the digits random images. After training. The 180 random images were recognized as the number 77 and the other numbers got better at their recognition.