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[D] Dealing with open set reidentification

What’s the best approach in dealing with open set identifications such as face id and re-id. I know these problems are still unsolved and give low results without human aid. So mainly Im asking for ideas on how to handle this topic. For the sake of the argument lets focus on face recognition and lets say all images are of high quality. So storing or comparing the first few hundred picture we might have somewhat okay results if we use clustering or threshholding but when the numbers get bigger the false positive rates sky rockets. So is there a way to rerank or retrain everyonce in a while. Or at least differentiate from known and unknowns. Im lost at this step.

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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.