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  2. Reverse image search - Wikipedia

    en.wikipedia.org/wiki/Reverse_image_search

    Puzzle is designed to offer reverse image search visually similar images, even after the images have been resized, re-compressed, recolored and/or slightly modified. [27] The image-match open-source project was released in 2016. The project, licensed under the Apache License, implements a reverse image search engine written in Python. [28]

  3. 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.

  4. 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 ...

  5. Google Image Labeler - Wikipedia

    en.wikipedia.org/wiki/Google_Image_Labeler

    Without human tagging of images, Google Images search has in the past relied on the filename of the image. For example, a photo that is captioned "Portrait of Bill Gates" might have "Bill Gates" associated as a possible search term. The Google Image Labeler relied on humans that tag the meaning or content of the image, rather than its context ...

  6. Google Search - Wikipedia

    en.wikipedia.org/wiki/Google_Search

    Google Search (also known simply as Google or Google.com) is a search engine operated by Google. It allows users to search for information on the Web by entering keywords or phrases. Google Search uses algorithms to analyze and rank websites based on their relevance to the search query. It is the most popular search engine worldwide.

  7. Content-based image retrieval - Wikipedia

    en.wikipedia.org/wiki/Content-based_image_retrieval

    General scheme of content-based image retrieval. Content-based image retrieval, also known as query by image content and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases (see this survey [1] for a scientific overview of the CBIR field).

  8. Wikipedia:Finding images tutorial - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Finding_images...

    An easy way to find such images is to search with the restriction to site:.gov OR site:.mil. Again, be creative and vary your search terms. Not all images on the .gov or .mil sites are public domain, however: works by local state governments are not necessarily in the public domain. In case of doubt, ask.

  9. Search engine results page - Wikipedia

    en.wikipedia.org/wiki/Search_engine_results_page

    The organic search results, queries, and advertisements are the three main components of the SERP, However, the SERP of major search engines, like Google, Yahoo!, Bing, and Sogou may include many different types of enhanced results (organic search, and sponsored) such as rich snippets, images, maps, definitions, answer boxes, videos or suggested search refinements.