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I am working on a problem where I have to identify small objects in high resolution images, and I was wondering on how to solve this problem.
Basically, I have at most a hundred high resolution images containing tiny objects I need to detect, and I was wondering if I should transform this problem into a supervised problem, where I would first label some images and then try some classification stuff, or whether I apply algorithms such as fast r-cnn.
As I cannot elaborate much more about the topic due to privacy concerns, I would like to know which approach would be the best, or how can I assess which approach to take.
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