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Friday, June 01, 2018

Researchers create photo filter that disables facial recognition | Planet Biometrics

Photo: Parham Aarabi
"Professor Parham Aarabi and graduate student Avishek Bose are using "neural net based constrained optimization" to disrupt face detection software" reports Planet Biometrics.

Photo: Planet Biometrics

The University of Toronto researchers used existing knowledge of detection software that says "small, often imperceptible, perturbations can be added to images to fool a typical classification network into misclassifying them." Their dynamic "attack" algorithm "produc[es] small perturbations that, when added to an input face image, causes the pre-trained face detector to fail."

Aarabi and Bose designed two different, opposing neural networks — one that attempts to identify faces and the other that works to "disrupt" that identification — using 'adversarial training', a deep learning technique that puts two opposing AI algorithms in a sort of digital cage match.
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Source: Planet Biometrics


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