Development of a Training Line Selection Procedure with Support for Compact Hypotheses in Characterization
DOI:
https://doi.org/10.61841/87mqj981Keywords:
Algorthim, Compact Hypotheses, Filexible Control Function Pattern Recognition, Training SetAbstract
This research paper explores the problem of improving the quality of recognition of objects by creating a selective study of the compact positioning of objects in solving problems of image identification. Image identification was done by refining the algorithm for the nearest neighbors. k is improved by introducing the flexible functionality of an adjacent algorithm. At the same time, the theory proposed by solving practical problems has been verified.
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