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See a monthly parameter usage report for Template:AI-generated in articles based on its TemplateData. TemplateData for AI-generated This tag is intended to identify articles that need extensive examination because they appear to have been generated using a large language model without rigorous scrutiny.
Reference Organizer presents all references in graphical user interface, where you can choose whether the references should be defined in the body of article or in the reference list template(s) (list-defined format). You can also sort the references in various ways (and optionally keep the sort order), and rename the references.
The easiest way to start citing on Wikipedia is to see a basic example. The example here will show you how to cite a newspaper article using the {} template (see Citation quick reference for other types of citations). Copy and paste the following immediately after what you want to reference:
Google Scholar, Google's search engine for academic papers and other scholarly research. Google Images, Google's search engine for images. Only images compatible with Wikipedia's licensing are included. Wikipedia Reference Search, a Google search that only searches sites vetted by Wikipedians. free news sources
See a monthly parameter usage report for Template:AI-generated inline in articles based on its TemplateData. TemplateData for AI-generated inline This tag is intended to identify articles that need extensive examination because they appear to have been generated using a large language model without rigorous scrutiny.
This template allows editors to tweak search strings to find the best match for the subject; see the documentation for details. Alternatively, users who desire more freedom can use the meta-template {{find sources multi}}, which allows a choice of search engines. Example of {{find sources}}:
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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).