会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 1. 发明申请
    • APPARATUS, SYSTEM, AND METHOD FOR OBJECT DETECTION AND IDENTIFICATION
    • 用于物体检测和识别的装置,系统和方法
    • US20120143808A1
    • 2012-06-07
    • US12959207
    • 2010-12-02
    • James P. KarinsStuart A. Mills
    • James P. KarinsStuart A. Mills
    • G06N5/02
    • G06N7/005
    • An apparatus, system, and method are disclosed for identifying a target object. An object detection module detects objects by matching data from one or more sensors to known data of a target object and determining one or more correlation metrics for each object. An object tracking module tracks geographic locations for detected objects over time using subsequent data from the one or more sensors. A contextual data module determines one or more contextual indicators for detected objects based on the data from the one or more sensors. An artificial intelligence module estimates probabilities that detected objects comprise the target object based on the correlation metrics, the geographic locations, the contextual indicators, and one or more target contextual indicators associated with the target object. The artificial intelligence module estimates the probabilities using an artificial intelligence model, such as a Bayesian network.
    • 公开了用于识别目标对象的装置,系统和方法。 对象检测模块通过将来自一个或多个传感器的数据与目标对象的已知数据进行匹配来检测对象,并确定每个对象的一个​​或多个相关度量。 对象跟踪模块使用来自一个或多个传感器的后续数据随时间跟踪检测到的对象的地理位置。 上下文数据模块基于来自一个或多个传感器的数据确定检测到的对象的一个​​或多个上下文指示符。 人造智能模块基于相关度量,地理位置,上下文指示符以及与目标对象相关联的一个或多个目标上下文指示来估计检测到的对象包括目标对象的概率。 人工智能模块使用诸如贝叶斯网络的人造智能模型来估计概率。
    • 2. 发明授权
    • Apparatus, system, and method for object detection and identification
    • 用于物体检测和识别的装置,系统和方法
    • US08527445B2
    • 2013-09-03
    • US12959207
    • 2010-12-02
    • James P. KarinsStuart A. Mills
    • James P. KarinsStuart A. Mills
    • G06N5/02
    • G06N7/005
    • An apparatus, system, and method are disclosed for identifying a target object. An object detection module detects objects by matching data from one or more sensors to known data of a target object and determining one or more correlation metrics for each object. An object tracking module tracks geographic locations for detected objects over time using subsequent data from the one or more sensors. A contextual data module determines one or more contextual indicators for detected objects based on the data from the one or more sensors. An artificial intelligence module estimates probabilities that detected objects comprise the target object based on the correlation metrics, the geographic locations, the contextual indicators, and one or more target contextual indicators associated with the target object. The artificial intelligence module estimates the probabilities using an artificial intelligence model, such as a Bayesian network.
    • 公开了用于识别目标对象的装置,系统和方法。 对象检测模块通过将来自一个或多个传感器的数据与目标对象的已知数据进行匹配来检测对象,并确定每个对象的一个​​或多个相关度量。 对象跟踪模块使用来自一个或多个传感器的后续数据随时间跟踪检测到的对象的地理位置。 上下文数据模块基于来自一个或多个传感器的数据确定检测到的对象的一个​​或多个上下文指示符。 人造智能模块基于相关度量,地理位置,上下文指示符以及与目标对象相关联的一个或多个目标上下文指示来估计检测到的对象包括目标对象的概率。 人工智能模块使用诸如贝叶斯网络的人造智能模型来估计概率。
    • 4. 发明授权
    • Fingerprint classification via spatial frequency components
    • 通过空间频率分量进行指纹分类
    • US06226391B1
    • 2001-05-01
    • US09350807
    • 1999-07-09
    • Robert Barry DydykStuart A. MillsPhillip Wayne Dennis
    • Robert Barry DydykStuart A. MillsPhillip Wayne Dennis
    • G06K900
    • G06K9/0008
    • The present invention is a method and apparatus for automatically placing a first unknown image, such as an unknown fingerprint image, into one of a plurality of categories. The invention includes storing in a library a plurality of value series, each of which series is derived from the frequency representation of an image category. The categorization process and apparatus takes the frequency image of a first unknown pattern to create a first frequency image. The frequency image plane of the first (unknown) frequency image is divided into a plurality of frequency image plane regions. Each of the frequency image plane regions may be an angular segment radiating from the origin of the frequency image plane. A region value is assigned to each of the frequency image plane regions based on the total energy in the frequency image in that region. The region values for the first frequency image are combined to generate a first series of region values. The first series of region values is compared in a comparator with each of the stored value series. The comparator preferably performs a correlation function on the pattern or series of the regional values using the one dimensional frequency transform of the spatial representation of the pattern of series of regional values.
    • 本发明是用于将第一未知图像(诸如未知指纹图像)自动放置在多个类别之一中的方法和装置。 本发明包括在库中存储多个值序列,其中每个序列从图像类别的频率表示中导出。 分类处理和装置采用第一未知图案的频率图像来创建第一频率图像。 第一(未知)频率图像的频率像平面被分成多个频率像平面区域。 每个频率像平面区域可以是从频率图像平面的原点辐射的角度段。 基于该区域中的频率图像中的总能量,将区域值分配给每个频率图像平面区域。 第一频率图像的区域值被组合以产生第一系列区域值。 在比较器中将第一系列区域值与每个存储值序列进行比较。 比较器优选地使用一系列区域值的模式的空间表示的一维频率变换来对区域值的模式或一系列进行相关函数。
    • 5. 发明授权
    • Adaptively aligned optical correlator and method
    • 自适应光学相关器和方法
    • US06330361B1
    • 2001-12-11
    • US09268789
    • 1999-03-16
    • Robert A. MitchellStuart A. MillsJames Ryan
    • Robert A. MitchellStuart A. MillsJames Ryan
    • G06K900
    • G06K7/14G06E3/005
    • An improved optical correlator using a coherent light beam employs a method of adaptive alignment. A test pattern modulates an input spatial light modulator. The modulated beam propagates through passive transforming optical elements to a filter spatial light modulator, which is simultaneously modulated with an independently transformed frequency domain reference. The resulting correlation or coincidence of the optically transformed pattern with the independently transformed reference is processed to yield a feedback signal indicative of any optical misalignment of the optical correlator. The feedback signal drives a beam deflector to compensate by adjusting the path of the coherent beam, thereby improving and maintaining optical alignment of the correlator.
    • 使用相干光束的改进的光学相关器采用自适应对准的方法。 测试模式调制输入空间光调制器。 调制的光束通过无源变换光学元件传播到过滤器空间光调制器,该调制器使用独立变换的频域参考来同时调制。 对光学变换图案与独立变换参考的相关或重合进行处理,以产生指示光学相关器的任何光学偏移的反馈信号。 反馈信号驱动光束偏转器以通过调整相干光束的路径进行补偿,从而改善和维持相关器的光学对准。
    • 6. 发明授权
    • Fingerprint classification via spatial frequency components
    • 通过空间频率分量进行指纹分类
    • US5953442A
    • 1999-09-14
    • US899803
    • 1997-07-24
    • Robert Barry DydykStuart A. MillsPhillip Wayne Dennis
    • Robert Barry DydykStuart A. MillsPhillip Wayne Dennis
    • G06T7/00G06K9/00
    • G06K9/0008
    • The present invention is a method and apparatus for automatically placing a first unknown image, such as an unknown fingerprint image, into one of a plurality of categories. The invention includes storing in a library a plurality of value series, each of which series is derived from the frequency representation of an image category. The categorization process and apparatus takes the frequency image of a first unknown pattern to create a first frequency image. The frequency image plane of the first (unknown) frequency image is divided into a plurality of frequency image plane regions. Each of the frequency image plane regions may be an angular segment radiating from the origin of the frequency image plane. A region value is assigned to each of the frequency image plane regions based on the total energy in the frequency image in that region. The region values for the first frequency image are combined to generate a first series of region values. The first series of region values is compared in a comparator with each of the stored value series. The comparator preferably performs a correlation function on the pattern or series of the regional values using the one dimensional frequency transform of the spatial representation of the pattern of series of regional values.
    • 本发明是用于将第一未知图像(诸如未知指纹图像)自动放置在多个类别之一中的方法和装置。 本发明包括在库中存储多个值序列,其中每个序列从图像类别的频率表示中导出。 分类处理和装置采用第一未知图案的频率图像来创建第一频率图像。 第一(未知)频率图像的频率像平面被分成多个频率像平面区域。 每个频率像平面区域可以是从频率图像平面的原点辐射的角度段。 基于该区域中的频率图像中的总能量,将区域值分配给每个频率图像平面区域。 第一频率图像的区域值被组合以产生第一系列区域值。 在比较器中将第一系列区域值与每个存储值序列进行比较。 比较器优选地使用一系列区域值的模式的空间表示的一维频率变换来对区域值的模式或一系列进行相关函数。