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  2. 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 ...

  3. 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.

  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. AOL Mail

    mail.aol.com

    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  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. digiKam - Wikipedia

    en.wikipedia.org/wiki/DigiKam

    Starting with version 2.0, digiKam has introduced face recognition allowing you to automatically identify photos of certain people and tag them. DigiKam's photo manager was the first free project to feature similar functionality, with face recognition previously implemented only in proprietary products such as Google Picasa, Apple's Photos, and Windows Live Photo Gallery.