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    • 3. 发明申请
    • METHOD AND SYSTEM FOR AUTOMATICALLY DIAGNOSING FAULTS IN RENDERING DEVICES
    • 用于自动诊断渲染设备中的故障的方法和系统
    • US20100325487A1
    • 2010-12-23
    • US12487803
    • 2009-06-19
    • Rajinderjeet Singh MinhasVishal MongaWencheng Wu
    • Rajinderjeet Singh MinhasVishal MongaWencheng Wu
    • G06F11/25G06N7/02
    • G06F11/2257
    • A method and system for automatically determining an optimal re-training interval for a fault diagnoser based on online monitoring of the performance of a classifier. The classifier generates a soft measure of membership in association with a class based on a training data. The output of the classifier can be utilized to assign a label to new data and then the members associated with each class can be clustered into one or more core members and potential outliers. A statistical measure can be utilized to determine if the distribution of the outliers is sufficiently different than the core members after enough outliers have been accumulated. If the outliers are different with respect to the core members, then the diagnoser can be re-trained; otherwise, the output of the classifier can be fed to the fault diagnoser.
    • 一种用于基于在线监视分类器的性能来自动确定故障诊断器的最佳再训练间隔的方法和系统。 分类器基于训练数据生成与类相关联的隶属度的软测量。 分类器的输出可以用于为新数据分配标签,然后与每个类相关联的成员可以聚类成一个或多个核心成员和潜在的异常值。 可以利用统计量度来确定离群点的分布是否充分地不同于核心成员在有足够的异常值累积之后。 如果异常值与核心成员不同,那么诊断者可以重新训练; 否则,分类器的输出可以馈送给故障诊断器。
    • 4. 发明授权
    • Method and system for automatically diagnosing faults in rendering devices
    • 自动诊断渲染设备故障的方法和系统
    • US08249830B2
    • 2012-08-21
    • US12487803
    • 2009-06-19
    • Rajinderjeet Singh MinhasVishal MongaWencheng WuDivyanshu Vats
    • Rajinderjeet Singh MinhasVishal MongaWencheng WuDivyanshu Vats
    • G21C17/00G06F11/30
    • G06F11/2257
    • A method and system for automatically determining an optimal re-training interval for a fault diagnoser based on online monitoring of the performance of a classifier are disclosed. The classifier generates a soft measure of membership in association with a class based on a training data. The output of the classifier can be utilized to assign a label to new data and then the members associated with each class can be clustered into one or more core members and potential outliers. A statistical measure can be utilized to determine if the distribution of the outliers is sufficiently different than the core members after enough outliers have been accumulated. If the outliers are different with respect to the core members, then the diagnoser can be re-trained; otherwise, the output of the classifier can be fed to the fault diagnoser.
    • 公开了一种基于在线监视分类器的性能来自动确定故障诊断器的最佳再训练间隔的方法和系统。 分类器基于训练数据生成与类相关联的隶属度的软测量。 分类器的输出可以用于为新数据分配标签,然后与每个类相关联的成员可以聚类成一个或多个核心成员和潜在的异常值。 可以利用统计量度来确定离群点的分布是否充分地不同于核心成员在有足够的异常值累积后。 如果异常值与核心成员不同,那么诊断者可以重新训练; 否则,分类器的输出可以馈送给故障诊断器。
    • 6. 发明授权
    • Intelligent use of scene and test pattern analyses for traffic camera diagnostics
    • 智能使用场景和测试模式分析用于交通摄像机诊断
    • US09060164B2
    • 2015-06-16
    • US13610907
    • 2012-09-12
    • Wencheng WuEdul N. Dalal
    • Wencheng WuEdul N. Dalal
    • H04N17/00G08G1/04
    • H04N17/002G08G1/04
    • A method for determining a response to misalignment of a camera monitoring a desired area includes acquiring temporal related frames from the camera including a reference frame. A pixel location is determined of a reference object from the frames. Using the pixel location of the reference object, a displacement of the camera between a current frame and the reference frame is determined. For the displacement exceeding a first threshold, a new displacement of the camera is measured by introducing at least one additional object to a camera field of view and comparing the new displacement to a second threshold. For the new displacement not exceeding the second threshold, the camera is recalibrated using a determined pixel location and a physical location of the at least one additional object. For the new displacement exceeding the second threshold, notification is provided of a misalignment to an associated user device.
    • 用于确定对监视所需区域的相机的未对准的响应的方法包括从摄像机获取包括参考帧的时间相关帧。 从帧中确定参考对象的像素位置。 使用参考对象的像素位置,确定相机在当前帧与参考帧之间的位移。 对于超过第一阈值的位移,通过将至少一个附加对象引入照相机视野并将新位移与第二阈值进行比较来测量照相机的新位移。 对于不超过第二阈值的新位移,使用确定的像素位置和至少一个附加对象的物理位置来重新校准照相机。 对于超过第二阈值的新位移,向相关联的用户设备通知未对准。
    • 10. 发明授权
    • Color management and calibration using a scanner or camera
    • 使用扫描仪或相机进行颜色管理和校准
    • US08797589B2
    • 2014-08-05
    • US12859760
    • 2010-08-19
    • Edul N. DalalWencheng Wu
    • Edul N. DalalWencheng Wu
    • G06K15/00G06F15/00H04N1/407H04N1/46G03F3/08
    • H04N1/6033G01J3/462
    • A computer-implemented method for color calibration and profiling of an output device includes measuring a color patch in a test pattern, which comprises a plurality of color patches, to obtain first image data; measuring the color patch in the test pattern to obtain second image data; transforming the first image data to a first estimated image data; determining a difference between the second image data and the first estimated image data to obtain a correction factor; and calculating, for each patch in the test pattern, a corrected image data by applying the correction factor to a subsequent estimated image data from the first sensor. The correction factor is used for correcting inaccuracies introduced when the first image data is transformed into the first estimated image data. The first image data and the second image data provide a measured color representation of the color patch in a device dependent color space and a device independent color space, respectively.
    • 用于颜色校准和输出设备的轮廓的计算机实现的方法包括测量包括多个色块的测试图案中的色块以获得第一图像数据; 测量测试图案中的色块以获得第二图像数据; 将所述第一图像数据变换为第一估计图像数据; 确定第二图像数据和第一估计图像数据之间的差以获得校正因子; 以及通过将所述校正因子应用于来自所述第一传感器的后续估计图像数据来计算所述测试图案中的每个贴片的校正图像数据。 校正因子用于校正当第一图像数据被变换为第一估计图像数据时引入的不精确度。 第一图像数据和第二图像数据分别在设备依赖的颜色空间和设备独立的颜色空间中分别提供色标的测量的颜色表示。