chuckbot
edit: Just realized you said 2/3 _fully connected layers_, which is right. But for convolutions we needed skip connections, too, to get them to work. Any reason you single out fully connected layers?
Saying "my code is more efficient than your code" might be acceptable, but saying "my code is efficient" drives me mad when it is used as a synonym for "my code is fast". Take a look at [1] and the note that this is not about optimization. Efficient algorithms are usually algorithms with close to optimal time or space complexitiy.
Python -> Cython speeds up you program but does not change the complexity of your algorithm.
k-means is not a mode seeking algorithm, I think. You are clustering your color space, but you're not even guaranteed to end up with colors that are very close to those in your image. With a high k you're getting actual colors in the image, but they're not really dominant anymore.
What about mean shift? It's based on one method of non-parametric density estimation. Another method is this: Some sort of histogramming, which is another method of non-parametric density estimation.
Also other colors spaces will pay off immensely.
int main(int argv, char **argv) {
return 0;
}
Doesn't look like CS and can't even be java. Adding a printf changes the top suggestion to perl. Adding an include changes the top suggestion to vala.The idea to reduce language recognition to syntax highlighting is a nice idea, but doesn't seem to work.