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  2. Google Lens - Wikipedia

    en.wikipedia.org/wiki/Google_Lens

    Lens can also use images to identify text and can find results from Google Search or translate the text with Google Translate in augmented reality. [9] Lens is also integrated with the Google Photos and Google Assistant apps. [5] The service originally launched as Google Goggles, a previous app that functioned similarly but with less capability.

  3. 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]

  4. Face detection - Wikipedia

    en.wikipedia.org/wiki/Face_detection

    A reliable face-detection approach based on the genetic algorithm and the eigen-face [4] technique: Firstly, the possible human eye regions are detected by testing all the valley regions in the gray-level image. Then the genetic algorithm is used to generate all the possible face regions which include the eyebrows, the iris, the nostril and the ...

  5. 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.

  6. DeepFace - Wikipedia

    en.wikipedia.org/wiki/DeepFace

    DeepFace systems can identify faces with 97% accuracy, almost the same accuracy as a human in the same position. Facebook's facial recognition is more effective than the FBI's technology, which has 85% accuracy. [9] Google's technology, FaceNet is more successful than DeepFace using the same data sets. FaceNet set a record for accuracy, 99.63%.

  7. 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.

  8. Face Recognition Grand Challenge - Wikipedia

    en.wikipedia.org/wiki/Face_Recognition_Grand...

    The Face Recognition Grand Challenge (FRGC) was a project that aimed to promote and advance face recognition technology to support existing face recognition efforts within the U.S. Government. The project ran from May 2004 to March 2006 and was open to face recognition researchers and developers in companies, academia, and research institutions.

  9. Reverse image search - Wikipedia

    en.wikipedia.org/wiki/Reverse_image_search

    An image search engine is a search engine that is designed to find an image. The search can be based on keywords, a picture, or a web link to a picture. The results depend on the search criterion, such as metadata, distribution of color, shape, etc., and the search technique which the browser uses.