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  2. List of facial expression databases - Wikipedia

    en.wikipedia.org/wiki/List_of_facial_expression...

    A facial expression database is a collection of images or video clips with facial expressions of a range of emotions.Well-annotated (emotion-tagged) media content of facial behavior is essential for training, testing, and validation of algorithms for the development of expression recognition systems.

  3. Google Lens - Wikipedia

    en.wikipedia.org/wiki/Google_Lens

    Google Lens is an image recognition technology developed by Google, designed to bring up relevant information related to objects it identifies using visual analysis based on a neural network. [2] First announced during Google I/O 2017, [ 3 ] it was first provided as a standalone app, later being integrated into Google Camera but was reportedly ...

  4. Google Photos - Wikipedia

    en.wikipedia.org/wiki/Google_Photos

    Google Photos is a photo sharing and storage service developed by Google.It was announced in May 2015 and spun off from Google+, the company's former social network.. Google Photos shares the 15 gigabytes of free storage space with other Google services, such as Google Drive and Gmail.

  5. 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]

  6. Face detection - Wikipedia

    en.wikipedia.org/wiki/Face_detection

    Face-detection algorithms focus on the detection of frontal human faces. It is analogous to image detection in which the image of a person is matched bit by bit. Image matches with the image stores in database. Any facial feature changes in the database will invalidate the matching process. [3] A reliable face-detection approach based on the ...

  7. DeepFace - Wikipedia

    en.wikipedia.org/wiki/DeepFace

    The input is an RGB image of the face, scaled to resolution , and the output is a real vector of dimension 4096, being the feature vector of the face image. In the 2014 paper, [ 13 ] an additional fully connected layer is added at the end to classify the face image into one of 4030 possible persons that the network had seen during training time.

  8. PhotoDNA - Wikipedia

    en.wikipedia.org/wiki/PhotoDNA

    The hashing method initially relied on converting images into a black-and-white format, dividing them into squares, and quantifying the shading of the squares, [5] did not employ facial recognition technology, nor could it identify a person or object in the image.

  9. PimEyes - Wikipedia

    en.wikipedia.org/wiki/PimEyes

    PimEyes is a facial recognition search website that allows users to identify all images on the internet of a person given a sample image. The website is owned by EMEARobotics, a corporation based in Dubai. The owner and CEO of EMEARobotics and PimEye is Giorgi Gobronidze, who is based in Tbilisi, Georgia. [1]