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Method of Multiple Instance Learning and Classification With Correlations in Object Detection

机译:目标检测中具有相关性的多实例学习与分类方法

摘要

A method for detecting an object within a structure includes performing tobogganing on image data to obtain one or more voxel clusters and to provide a rough indication of the structure. Each of the obtained voxel clusters is characterized as an object candidate and a set of features are determined for each object candidate. Correlations between pairs of the object candidates are measured. Each of the object candidates is classified as either a true object or a non-object based on the set of features and the measured correlations.
机译:一种用于检测结构内的物体的方法,包括对图像数据执行雪橇运动以获得一个或多个体素簇并提供该结构的粗略指示。将每个获得的体素簇表征为候选对象,并为每个候选对象确定一组特征。测量成对的候选对象之间的相关性。根据一组特征和测得的相关性,将每个候选对象分类为真实对象或非对象。

著录项

  • 公开/公告号US2008125648A1

    专利类型

  • 公开/公告日2008-05-29

    原文格式PDF

  • 申请/专利权人 JINBO BI;JIANMING LIANG;

    申请/专利号US20070944827

  • 发明设计人 JIANMING LIANG;JINBO BI;

    申请日2007-11-26

  • 分类号A61B6/03;G01N23/083;

  • 国家 US

  • 入库时间 2022-08-21 20:13:53

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