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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.
Fast Duplicate File Finder is a Windows tool developed by MindGems Inc, available as a freeware version and a full commercial version. It is intended to scan a user's computer for duplicate files, display a list of such files and let the user delete unneeded copies with the purpose of freeing up hard drive space.
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 ...
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.
In computer science, SimHash is a technique for quickly estimating how similar two sets are. The algorithm is used by the Google Crawler to find near duplicate pages. It was created by Moses Charikar.
Extra features: duplicate file finder module, faster byte-to-byte disk backups and much more; 4.0.0 Windows August 2019 Improved data protection; New image file formats; File labeling added; Expanded Disk Image support; Bitlocker support; New UI; Improved file previewing module; 4.0.123 [17] macOS October 2020 macOS Big Sur support; iOS 14 support
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The scheme was published by Andrei Broder in a 1997 conference, [1] and initially used in the AltaVista search engine to detect duplicate web pages and eliminate them from search results. [2] It has also been applied in large-scale clustering problems, such as clustering documents by the similarity of their sets of words. [1]