23 March 1993 Preprocessing remotely sensed data for efficient analysis and classification
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Interpreting remotely sensed data typically requires expensive, specialized computing machinery capable of storing and manipulating large amounts of data quickly. In this paper, we present a method for accurately analyzing and categorizing remotely sensed data on much smaller, less expensive platforms. Data size is reduced in such a way as to retain the integrity of the original data, where the format of the resultant data set lends itself well to providing an efficient, interactive method of data classification.
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Patrick M. Kelly, James M. White, "Preprocessing remotely sensed data for efficient analysis and classification", Proc. SPIE 1963, Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry, (23 March 1993); doi: 10.1117/12.141745; https://doi.org/10.1117/12.141745

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