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    • 11. 发明授权
    • Wafer inspection systems and methods for analyzing inspection data
    • 晶圆检查系统和检验数据分析方法
    • US07227628B1
    • 2007-06-05
    • US10964585
    • 2004-10-12
    • Paul SullivanGeorge KrenEliezer RosengausPatrick HuetRobinson PiramuthuMartin PlihalYan Xiong
    • Paul SullivanGeorge KrenEliezer RosengausPatrick HuetRobinson PiramuthuMartin PlihalYan Xiong
    • G01N21/88G06K9/00
    • G01N21/9501G01N21/9503H01L21/67005H01L21/67288
    • Wafer inspection systems and methods are provided. One inspection system includes a module measurement cell coupled to a host inspection system by a wafer handler. The module measurement cell is configured to inspect a wafer using one or more modes prior to inspection of the wafer by the host inspection system. The one or more modes include backside inspection, edge inspection, frontside macro defect inspection, or a combination thereof. Another inspection system includes two or more low resolution electronic sensors arranged at multiple viewing angles. The sensors are configured to detect light returned from a wafer substantially simultaneously. A method for analyzing inspection data includes selecting a template corresponding to a support device that contacts a backside of a wafer prior to inspection of the backside of the wafer. The method also includes subtracting data representing the template from inspection data generated by inspection of the backside of the wafer.
    • 提供晶圆检查系统和方法。 一个检查系统包括通过晶片处理器耦合到主机检查系统的模块测量单元。 模块测量单元被配置为在主机检查系统检查晶片之前使用一种或多种模式来检查晶片。 一种或多种模式包括后侧检查,边缘检查,前侧宏观缺陷检查或其组合。 另一种检查系统包括以多个视角布置的两个或多个低分辨率电子传感器。 传感器被配置为基本上同时检测从晶片返回的光。 用于分析检查数据的方法包括在检查晶片的背面之前选择与支撑装置相对应的模板,所述支撑装置接触晶片的背面。 该方法还包括从通过检查晶片的背面产生的检查数据中减去表示模板的数据。
    • 16. 发明授权
    • Method and system for hierarchical tissue analysis and classification
    • 分层组织分析和分类的方法和系统
    • US08600143B1
    • 2013-12-03
    • US13112977
    • 2011-05-20
    • Ashok V. KulkarniScott YoungEliezer Rosengaus
    • Ashok V. KulkarniScott YoungEliezer Rosengaus
    • G06K9/00
    • G06K9/6219G06K9/00147G06K9/34G06T7/11G06T7/143G06T2207/10004G06T2207/10056G06T2207/20076G06T2207/20081G06T2207/30024
    • The present invention may include segmenting an image at a first resolution level and a second resolution level, wherein one or more parameters of a segmentation algorithm are trainable via user classification feedback, extracting features from a first plurality of segment primitives and a second plurality of segment primitives, wherein one or more parameters of a segment feature extraction algorithm are trainable via user classification feedback, building a first and second segmentation hierarchy by generating one or more clusters of the first plurality of segment primitives and the second plurality of segment primitives, extracting one or more features from the first segmentation hierarchy and the second segmentation hierarchy utilizing a hierarchy feature extraction algorithm, determining an inter-level relationship between the clusters generated for the first resolution level and the second level, and automatically classifying one or more tissue elements of the tissue specimen via a user-trained classification algorithm.
    • 本发明可以包括以第一分辨率级别和第二分辨率级别分割图像,其中分割算法的一个或多个参数可经由用户分类反馈进行训练,从第一多个片段原语和第二多个片段中提取特征 原语,其中段特征提取算法的一个或多个参数可经由用户分类反馈进行训练,通过生成第一多个段原语和第二多个段原语中的一个或多个簇来构建第一和第二分段层级,提取一个 或更多来自第一分割层次和第二分段层次的特征,使用层次特征提取算法,确定为第一分辨率水平和第二水平生成的簇之间的层间关系,并且自动分类一个或多个组织元素 组织标本通过 用户训练的分类算法。