Development of a Training Line Selection Procedure with Support for Compact Hypotheses in Characterization

In 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.