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  2. DeepFace - Wikipedia

    en.wikipedia.org/wiki/DeepFace

    DeepFace is a deep learning facial recognition system created by a research group at Facebook. It identifies human faces in digital images. It identifies human faces in digital images. The program employs a nine-layer neural network with over 120 million connection weights and was trained on four million images uploaded by Facebook users.

  3. Facial recognition system - Wikipedia

    en.wikipedia.org/wiki/Facial_recognition_system

    Facial recognition software at a US airport Automatic ticket gate with face recognition system in Osaka Metro Morinomiya Station. A facial recognition system [1] is a technology potentially capable of matching a human face from a digital image or a video frame against a database of faces.

  4. Category:Facial recognition software - Wikipedia

    en.wikipedia.org/wiki/Category:Facial...

    Pages in category "Facial recognition software" The following 27 pages are in this category, out of 27 total. ... DeepFace; Heather Dewey-Hagborg; F. Face ID; Face.com;

  5. Face detection - Wikipedia

    en.wikipedia.org/wiki/Face_detection

    Face detection is gaining the interest of marketers. A webcam can be integrated into a television and detect any face that walks by. The system then calculates the race, gender, and age range of the face. Once the information is collected, a series of advertisements can be played that is specific toward the detected race/gender/age.

  6. Deepfake video app Reface is just getting started on ... - AOL

    www.aol.com/news/deepfake-video-app-reface-just...

    Deepface technology has of course been around for a number of years, at this point, but the Reface team's focus is on making the tech accessible and easy to use -- serving it up as a push-button ...

  7. FaceNet - Wikipedia

    en.wikipedia.org/wiki/FaceNet

    FaceNet is a facial recognition system developed by Florian Schroff, Dmitry Kalenichenko and James Philbina, a group of researchers affiliated with Google.The system was first presented at the 2015 IEEE Conference on Computer Vision and Pattern Recognition. [1]

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