Artificial Intelligence Asked on December 30, 2021
I am trying to classify tampered, pristine images from set of images, in that I have built a network in which I would divide the image into multiple overlapping patches and then classify them into pristine or fake(based on the probability outputs), but now I want extend the same to Image level. That is I want to build some model or some rule over output probabilities of patches of each image to get probability that the image is fake or pristine.
ways I am thinking to do is –
I can’t really say which among the above three is better or worse, I don’t even know the possibility of the above three. (Kind of hit a roadblock in thinking)
Now the question am I thinking in right direction, what would be better among the ideas I am considering and why. Is there anything better than what I am thinking. It would helpful in suggesting some resources.
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