I have two groups of images, each one with 1000 samples.
The speckle pattern, in this context, is the same as a random pattern or "white noise" image. So these images are fundamentally different.
In group one, each figure is generated by considering a random function that returns something similar to a speckle pattern (see fig. 1). In group two we follow the same procedure as group 1, but we plot a small point above that can be positioned anywhere and with any color (see fig. 2).
I want to classify both groups and I already tried to do it with simple neural networks, but I have been unsuccessful.
What is the best technique for this kind of problems?