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Google Scholar is a freely accessible web search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines. . Released in beta in November 2004, the Google Scholar index includes peer-reviewed online academic journals and books, conference papers, theses and dissertations, preprints, abstracts, technical reports, and other ...
List of academic databases and search engines. This article contains a representative list of notable databases and search engines useful in an academic setting for finding and accessing articles in academic journals, institutional repositories, archives, or other collections of scientific and other articles. Databases and search engines differ ...
Search engine tests. Depending on the subject matter, and how carefully it is used, a search engine test can be very effective and helpful, or produce misleading or non-useful results. In most cases, a search engine test is a first-pass heuristic or " rule of thumb ".
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Open-source desktop search tool for Unix/Linux GPL Google Desktop: Linux, Mac OS X, Windows: Integrates with the main Google search engine page. As of September 14, 2011, Google has discontinued this product. Freeware ISYS Search Software: Windows: ISYS:Desktop search software. Proprietary (14-day trial) KRunner: Linux: Locate32: Windows
Time period. Development. 1996–1997. Development of basic technology, launch of search engine, attachments like gmail and classroom come later. 2000. Internationalization: search is launched in 13 new languages. 2001–2004. Google launches many new search categories, such as Google News, Google Books, and Google Scholar . 2002 onward.
Google News, Google Books, and Google Scholar provide results that are more likely to be reliable sources, but only if these hits are able to be verified and are reliable sources by reading the articles or books. While all of them may not be able to be viewed on the Google site itself, and many of them are previews, the search can at least show ...
Since the kernel output is the same length as width, its area is 55×55.) AlexNet is the name of a convolutional neural network (CNN) architecture, designed by Alex Krizhevsky in collaboration with Ilya Sutskever and Geoffrey Hinton, who was Krizhevsky's Ph.D. advisor at the University of Toronto. [1] [2]