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  1. TinEye. TinEye is an image search and recognition company. We are experts in computer vision, pattern recognition, neural networks, and machine learning. Our mission is to make your images searchable. How to use TinEye

    • Extensions

      TinEye is an image search and recognition company. We are...

    • Images Search

      Non è possibile visualizzare una descrizione perché il sito...

    • Technology

      TinEye offers a number of computer vision, image recognition...

    • Products

      TinEye is an image search and recognition company. We are...

    • About

      Our culture. Our clients come first.Always. We are...

    • How to Use TinEye

      How to use TinEye. Using TinEye, you can search by image or...

    • FAQs

      TinEye is a reverse image search engine. You can submit an...

    • Help Center

      FAQs and help docs for TinEye API clients

  2. en.wikipedia.org › wiki › TinEyeTinEye - Wikipedia

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

  3. You can use TinEye to search for an online image by pasting its “image URL” into the search box. An image URL is an internet address that points directly to a specific image, rather than an entire index, webpage or website.

  4. 25 lug 2017 · TinEye is the original reverse image search engine, using image recognition with a growing index of billions of images. You can use TinEye to find out where an image came from, how it is being used, if modified versions of the image exist, or to find a higher resolution version.

  5. TinEye è un motore di ricerca con intelligenza artificiale che, sfruttando un database di quasi 40 miliardi di immagini, permette di trovare tutti i siti dove è stata pubblicata una specifica immagine. Possiamo anche utilizzare il servizio nel caso in cui trovassimo un’immagine con bassa risoluzione.

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