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  2. Viola–Jones object detection framework - Wikipedia

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

    The Viola–Jones object detection framework is a machine learning object detection framework proposed in 2001 by Paul Viola and Michael Jones. [1] [2] It was motivated primarily by the problem of face detection, although it can be adapted to the detection of other object classes. In short, it consists of a sequence of classifiers.

  3. 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.

  4. 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]

  5. Amazon Rekognition - Wikipedia

    en.wikipedia.org/wiki/Amazon_Rekognition

    Celebrity recognition in images [3] [4]; Facial attribute detection in images, including gender, age range, emotions (e.g. happy, calm, disgusted), whether the face has a beard or mustache, whether the face has eyeglasses or sunglasses, whether the eyes are open, whether the mouth is open, whether the person is smiling, and the location of several markers such as the pupils and jaw line.

  6. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    This is a list of datasets for machine learning research. It is part of the list of datasets for machine-learning research . These datasets consist primarily of images or videos for tasks such as object detection , facial recognition , and multi-label classification .

  7. 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]

  8. Deepfake - Wikipedia

    en.wikipedia.org/wiki/Deepfake

    Shamook, then, created a 180 degree facial profile that he fed into a machine learning piece of software (DeepFaceLabs), along with Tom Hanks' face from Forrest Gump. [271] The humor and irony of this deepfake traces back to 2007 when John Travolta revealed he turned down the chance to play the lead role in Forrest Gump because he had said yes ...

  9. Face detection - Wikipedia

    en.wikipedia.org/wiki/Face_detection

    In object-class detection, the task is to find the locations and sizes of all objects in an image that belong to a given class. Examples include upper torsos, pedestrians, and cars. Face detection simply answers two question, 1. are there any human faces in the collected images or video? 2. where is the face located?