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  2. Face detection - Wikipedia

    en.wikipedia.org/wiki/Face_detection

    Face detection is a computer technology being used in a variety of applications that identifies human faces in digital images. [1] Face detection also refers to the psychological process by which humans locate and attend to faces in a visual scene.

  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. OpenCV - Wikipedia

    en.wikipedia.org/wiki/OpenCV

    The first alpha version of OpenCV was released to the public at the IEEE Conference on Computer Vision and Pattern Recognition in 2000, and five betas were released between 2001 and 2005. The first 1.0 version was released in 2006. A version 1.1 "pre-release" was released in October 2008.

  5. Object detection - Wikipedia

    en.wikipedia.org/wiki/Object_detection

    Objects detected with OpenCV's Deep Neural Network module (dnn) by using a YOLOv3 model trained on COCO dataset capable to detect objects of 80 common classes. Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos. [1]

  6. 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]

  7. Viola–Jones object detection framework - Wikipedia

    en.wikipedia.org/wiki/Viola–Jones_object...

    The job of each stage is to determine whether a given sub-window is definitely not a face or may be a face. A given sub-window is immediately discarded as not a face if it fails in any of the stages. A simple framework for cascade training is given below: f = the maximum acceptable false positive rate per layer.

  8. Fawkes (software) - Wikipedia

    en.wikipedia.org/wiki/Fawkes_(software)

    Facial recognition works by pinpointing unique dimensions of facial features, which are then rendered as a vector graphic image of the face. Fawkes is a facial image cloaking software created by the SAND (Security, Algorithms, Networking and Data) Laboratory of the University of Chicago . [ 1 ]

  9. 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. 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.