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  2. 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.

  3. TinEye - Wikipedia

    en.wikipedia.org/wiki/TinEye

    TinEye is a reverse image search engine developed and offered by Idée, Inc., a company based in Toronto, Ontario, Canada. It is the first image search engine on the web to use image identification technology rather than keywords, metadata or watermarks. [1] [non-primary source needed] TinEye allows users to search not using keywords but with ...

  4. AOL

    search.aol.com

    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.

  5. Google Images - Wikipedia

    en.wikipedia.org/wiki/Google_Images

    Google Images (previously Google Image Search) is a search engine owned by Gsuite 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.

  6. How to do a reverse image search - AOL

    www.aol.com/lifestyle/reverse-image-search...

    Alternately, the website reverse.photos has a simple interface for uploading photos that automatically passes your search through Google’s reverse image search. Method 3: Bing Images. Mobile ...

  7. Image retrieval - Wikipedia

    en.wikipedia.org/wiki/Image_retrieval

    An image retrieval system is a computer system used for browsing, searching and retrieving images from a large database of digital images. Most traditional and common methods of image retrieval utilize some method of adding metadata such as captioning, keywords, title or descriptions to the images so that retrieval can be performed over the annotation words.

  8. ImageNet - Wikipedia

    en.wikipedia.org/wiki/ImageNet

    They had enough budget to have each of the 14 million images labelled three times. [10] The original plan called for 10,000 images per category, for 40,000 categories at 400 million images, each verified 3 times. They found that humans can classify at most 2 images/sec. At this rate, it was estimated to take 19 human-years of labor (without ...

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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.