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In June 2011, Google Images added a "Search by Image" feature which allowed for reverse image searches directly in the image search-bar without third-party add-ons. This feature allows users to search for an image by dragging and dropping one onto the search bar, uploading one, or copy-pasting a URL that points to an image into the search bar. [12]
When you do a reverse image search on Google, you place a photo, or a link to a photo, in the search bar instead of a text query. Google then finds websites featuring your image as well as related ...
Image search is a specialized data search used to find images. To search for images, a user may provide query terms such as keyword, image file/link, or click on some image, and the system will return images "similar" to the query. The similarity used for search criteria could be meta tags, color distribution in images, region/shape attributes ...
An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
This page explains how to place images on wiki pages, where the image acts as a hypertext link to somewhere other than the image description page. Care should be taken that this is done in compliance with the licensing terms of the file in question, particularly if they require proper attribution.
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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).
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