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System and method of chaining algorithms for global object recognition to improve probability of correctness and reduce processing load

机译:用于全局对象识别的链接算法的系统和方法,以提高正确性的可能性并减少处理负荷

摘要

A system and method improves the probability of correctly detecting an object from a collection of source data and reduces the processing load. A plurality of algorithms for a given data type are selected and ordered based on a cumulative trained probability of correctness (Pc) that each of the algorithms, which are processed in a chain and conditioned upon the result of the preceding algorithms, produce a correct result and a processing. The algorithms cull the source data to pass forward a reduced subset of source data in which the conditional probability of detecting the object is higher than the a priori probability of the algorithm detecting that same object. The Pc and its confidence interval is suitably computed and displayed for each algorithm and the chain and the final object detection.
机译:一种系统和方法提高了从源数据的集合中正确检测对象的可能性,并减少了处理负荷。根据累积的训练正确性概率(Pc)选择和排序给定数据类型的多种算法,其中,每个算法(按链进行处理并以先前算法的结果为条件)产生正确的结果和处理。该算法剔除源数据以转发源数据的缩小子集,其中,检测到对象的条件概率高于算法检测到同一对象的先验概率。对于每种算法以及链和最终目标检测,将适当地计算和显示Pc及其置信区间。

著录项

  • 公开/公告号US10460252B2

    专利类型

  • 公开/公告日2019-10-29

    原文格式PDF

  • 申请/专利权人 RAYTHEON COMPANY;

    申请/专利号US201615053959

  • 申请日2016-02-25

  • 分类号G06F17/30;G06N7;G06N20;G06F16/29;G06F16/583;

  • 国家 US

  • 入库时间 2022-08-21 12:15:07

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