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The simplest of all retrieval techniques is the text-based searching where the information about the multimedia data is stored with the data file.
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To make the retrieval system automated, efficient, and intelligent, content-based retrieval techniques were introduced.
Almost all the 3D retrieval techniques are resource (time and memory) demanding prior to achieve recognition and ranking.
In order to overcome this shortcoming of these techniques, image retrieval techniques are strongly focused on content-based image retrieval (CBIR).
Following deparaffinization, heat-induced antigen retrieval techniques were used.
In addition, retrieval techniques were unable to reinstate the fear response.
However, given the vastness of the literature and an accelerating publication rate, manual techniques and conventional information retrieval techniques are unable to deliver timely, reliable, exhaustive and specific results.
The retrieval technique is described and a detailed error analysis is given.
The satellite rainfall retrieval technique is based on various spectral parameters of SEVIRI that express microphysical and optical cloud properties.
The feature based reranking algorithm for image similarity prediction using query-context bag-of-object retrieval technique is discussed in [33].
However, because no operational retrieval technique is currently available for MSG SEVIRI, that is applicable to water and ice clouds, and that is fast enough concerning the 15-min scan cycle, the authors decided to use the original reflectance of cannel (VIS0.6) and cannel (NIR1.6) SEVIRI channels, instead of computed values of effective droplet radius and optical thickness of clouds.
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