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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. How to do a reverse image search - AOL

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

   If you use Google Chrome as your primary browser, the easiest way to complete a reverse image search is through Google Images. Just right-click the image and select “Search Google for image ...

4. Google Images - Wikipedia

   en.wikipedia.org/wiki/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. [2] [3] [4] In 2011, reverse image search functionality was added.

5. TinEye - Wikipedia

   en.wikipedia.org/wiki/TinEye

   Active. 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] TinEye allows users to search not using keywords but with images.

6. List of CBIR engines - Wikipedia

   en.wikipedia.org/wiki/List_of_CBIR_engines

   Commercial CBIR search engines. Smart image searcher with content-based clustering in a visual network. CBIR search engine, by Imense. CBIR search engine, by Imprezzeo. Product comparison & shopping using CBIR for product images. Previously known as Pixsta. CBIR service tracks image usage across the web.

7. Content-based image retrieval - Wikipedia

   en.wikipedia.org/wiki/Content-based_image_retrieval

   VisualRank is a system for finding and ranking images by analysing and comparing their content, rather than searching image names, Web links or other text. Google scientists made their VisualRank work public in a paper describing applying PageRank to Google image search at the International World Wide Web Conference in Beijing in 2008.