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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. 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.

  4. TinEye - Wikipedia

    en.wikipedia.org/wiki/TinEye

    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 ...

  5. How to do a reverse image search - AOL

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

    Method 1: Google Images From a Desktop Computer. 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 ...

  6. Computer vision - Wikipedia

    en.wikipedia.org/wiki/Computer_vision

    Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images, and extraction of high-dimensional data from the real world in order to produce numerical or symbolic information, e.g. in the forms of decisions. [1][2][3][4] Understanding in this context means the transformation of visual images (the ...

  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. Searx - Wikipedia

    en.wikipedia.org/wiki/Searx

    Searx. Searx (/ sɜːrks /; stylized as searX) is a free and open-source metasearch engine, [4] available under the GNU Affero General Public License version 3, with the aim of protecting the privacy of its users. [5][6][7] To this end, Searx does not share users' IP addresses or search history with the search engines from which it gathers results.

  9. List of Yandex products and services - Wikipedia

    en.wikipedia.org/wiki/List_of_Yandex_products...

    Yandex Metro Yandex Music: Music streaming service [12] Yandex News: News aggregator [13] Yandex Panoramas Yandex Pay Payment service Yandex Search: Search engine [14] Yandex Taxi: Taxi aggregation [15] Yandex Timetable Yandex Traffic Yandex Translate: Multilingual neural machine translation [16] Yandex Video Shedevrum AI-generated images