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It's not excellent research. All they did is create a naive NN without any feature recognition and noted that it has a high rate of false positives when presented with random imagery. Duh.


Really? From the article:

"They tested with two widely used DNN systems that have been trained on massive image databases."

Is this wrong?


GIGO. Just because they used a "Deep" architecture doesn't mean it was suitable for the task.


Does your criticism extend to the whole enterprise of facial recognition, or did this research somehow fail to include the secret sauce that makes it work?




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