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  2. Reverse image search - Wikipedia

    en.wikipedia.org/wiki/Reverse_image_search

    A visual search engine is a search engine designed to search for information on the World Wide Web through a reverse image search. Information may consist of web pages, locations, other images and other types of documents. This type of search engines is mostly used to search on the mobile Internet through an image of an unknown object (unknown ...

  3. Google Images - Wikipedia

    en.wikipedia.org/wiki/Google_Images

    Google Images. Google Images (previously Google Image Search) is a search engine owned by Google that allows users to search the World Wide Web for images. [1] It was introduced on July 12, 2001, due to a demand for pictures of the green Versace dress of Jennifer Lopez worn in February 2000.

  4. Google Search - Wikipedia

    en.wikipedia.org/wiki/Google_Search

    Google Real-Time Search was a feature of Google Search in which search results also sometimes included real-time information from sources such as Twitter, Facebook, blogs, and news websites. [171] The feature was introduced on December 7, 2009, [ 172 ] and went offline on July 2, 2011, after the deal with Twitter expired. [ 173 ]

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    You can find instant answers on our AOL Mail help page. Should you need additional assistance we have experts available around the clock at 800-730-2563.

  6. Facial recognition system - Wikipedia

    en.wikipedia.org/wiki/Facial_recognition_system

    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. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image.

  7. AOL

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    The search engine that helps you find exactly what you're looking for. Find the most relevant information, video, images, and answers from all across the Web. AOL.

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  9. FaceNet - Wikipedia

    en.wikipedia.org/wiki/FaceNet

    FaceNet. FaceNet is a facial recognition system developed by Florian Schroff, Dmitry Kalenichenko and James Philbina, a group of researchers affiliated to Google. The system was first presented in the IEEE Conference on Computer Vision and Pattern Recognition held in 2015. [1] The system uses a deep convolutional neural network to learn a ...

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