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> The dataset does not link the photos of people’s faces to their names, which means any system trained to use the photos would not be able to identify named in
by philipodonnell 8y ago
> The dataset does not link the photos of people’s faces to their names, which means any system trained to use the photos would not be able to identify named individuals.
But isn't that like the point of a facial recognition algorithm? Recognizing individuals by their faces? Presumably from a reference image that has a name?
Also it seems pretty trivial to reverse lookup the images if they were from a public source and some of those will have names, unless they are significantly downsampled.
- deleted 8y ago[deleted]
- fixermark 8y agoNot necessarily. One thing that a wide-net dataset can be extremely useful for is improving the neural net models to better recognize people outside the traditional academic dataset a lot of older-generation neural nets were trained on, which is to say: the sorts of people who have the time and need-awareness to put their faces in some university's dataset for training neural nets (which is to say: white guys ;) ). You can use faces without names attached to improve the engine's modeling for recognizing human faces in general (and more importantly: improve the system's ability to distinguish human and animal faces). (Your first comment is pretty interesting by itself, incidentally: both NBC News and your comment make an assumption that is not universially true about the technology. Face recognition is a much wider space than "recognize an individual by their face." Clustering of similar faces, emotion analysis, camera targeting, human presence / absence can all be done without name labels).