I was wondering if machine learning algorithms (CNNs?) can be used/trained to differentiate between small differences in details between images (such as slight differences in shades of red or other colours, or the presence of small objects between otherwise very similar images?)? And then classify images based on these differences? If this is a difficult endeavour with our current machine learning algorithms, how can it be solved? Would using more data (more images) help?
I would also appreciate it if people could please provide references to research that has focused on this, if possible.
I've only just begun learning machine learning, and this is something that I've been wondering from my research.