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    • 2. 发明授权
    • Deinterlacing video images with slope detection
    • 用斜率检测去隔行视频图像
    • US07339626B2
    • 2008-03-04
    • US10862215
    • 2004-06-07
    • Hong JiangKim N. MatthewsLesley Jen-Yuan WuXiaoyun Wu
    • Hong JiangKim N. MatthewsLesley Jen-Yuan WuXiaoyun Wu
    • H04N7/01
    • H04N5/142H04N7/012
    • An apparatus and method for deinterlacing video images with improved slope detection is described. In one exemplary implementation, the apparatus includes an input buffer, a processor, and an output buffer. The input buffer is configured to receive a video stream in an interlaced format. The processor is configured to convert the video stream from the interlaced format to a progressive format. This conversion process includes calculating the slope for a diagonal line of an image at a pixel to-be-interpolated (i.e., at a missing pixel) using a slope protection operation to increase the accuracy of the slope calculation. The output buffer is then configured to transmit the video stream in the progressive format.
    • 描述了一种用于具有改进的斜率检测的用于去隔行视频图像的装置和方法。 在一个示例性实现中,该装置包括输入缓冲器,处理器和输出缓冲器。 输入缓冲器被配置为以隔行格式接收视频流。 处理器被配置为将视频流从隔行格式转换成渐进格式。 该转换处理包括使用斜率保护操作来计算要被内插的像素(即,在缺失像素处)的图像的对角线的斜率,以增加斜率计​​算的精度。 然后,输出缓冲器被配置为以逐行格式发送视频流。
    • 4. 发明授权
    • Distribution of parameter calculation for iterative optimization methods
    • 迭代优化方法的参数计算分布
    • US09015083B1
    • 2015-04-21
    • US13428985
    • 2012-03-23
    • Rajat MongaXiaoyun WuAndrew Yan-Tak Ng
    • Rajat MongaXiaoyun WuAndrew Yan-Tak Ng
    • G06N7/00G06F17/17
    • G06F17/10G06F17/17G06F17/18G06F17/5009G06N7/005G06N99/005
    • Systems and methods are disclosed for distributed first- or higher-order model fitting algorithms. Determination of the parameter set for the objective function is divided into a plurality of sub-processes, each performed by one of a plurality of worker computers. A master computer coordinates the operation of the plurality of worker computers, each operating on a portion of the parameter set such that no two worker computers contain exactly the same parameter subset nor the complete parameter set. Each worker computer performs its sub-processes on its parameter subset, together with training data. For maximum efficiency, the sub-processes are performed using a compact set of instruction primitives. The results are evaluated by the master computer, which may coordinate additional sub-process operations to perform higher-order optimization or terminate the optimization method and proceed to formulation of a model function.
    • 公开了分布式一阶或更高阶模型拟合算法的系统和方法。 确定目标函数的参数集被划分为多个子进程,每个子进程由多个工作计算机之一执行。 主计算机协调多个工作计算机的操作,每个操作计算机在参数集的一部分上操作,使得没有两个工作计算机包含完全相同的参数子集和完整的参数集。 每个工作计算机在其参数子集上与训练数据一起执行其子进程。 为了最大限度地提高效率,使用一组紧凑的指令原语执行子进程。 结果由主计算机评估,主计算机可以协调附加的子过程操作以执行更高阶优化或终止优化方法并且继续制定模型函数。