Search - mean shift

Search - mean shift - List

[Other resource] edison_binary DL : 0: 关于均值漂移的程序，该代码为编译好的程序，可以直接看图像分割效果！-Mean Shift on the procedures, the code compiled procedures, can look directly image segmentation results!
Date : 2008-10-13 Size : 1.42mb User : 曹刚
[Other resource] Mean-ShiftClustering DL : 0: mean shift算法在聚类中的matlab实现-mean shift clustering algorithm to achieve the Matlab
Date : 2008-10-13 Size : 3.18kb User : 陈彪
[Other resource] Mean-Shift DL : 0: mean-shift算法的实现算例，通过看这段代码，可以很快熟悉mean-shift算法-mean-shift method for the example, look at this code can be quickly familiar with the mean-shift algorithm
Date : 2008-10-13 Size : 77.29kb User : 胖丫
[Other resource] MeanShiftTracking DL : 1: 国外一个大牛人写的MEAN-SHIFT目标跟踪算法，程序使用了OPENCV函数库。-abroad a large cattle written by MEAN - SHIFT target tracking algorithm, OPENCV procedures for the use of the libraries.
Date : 2008-10-13 Size : 104.49kb User : 贾翔
[Other resource] chinachess DL : 0: 棋盘信息无疑会快于90个字节的棋盘，但这并不意味着所有的运算和操作都会更快。使用32个字节的数据表示，程序员在确定一个棋子的位置时往往需要增加额外的移位操作以取出一个字节中含有的两个坐标信息。2.2 比特棋盘（BitBoards）随着计算机存储能力的大幅提高，棋盘表示的空间需求往往已不是设计人员最为关注的问题。-chessboard information will undoubtedly faster than 90 bytes of chessboard. But this does not mean that all arithmetic operations and will be faster. Using 32 bytes of data, programmers in determining the location of a piece often need additional shift operation to remove a byte containing the 2 Coordinate information. 2.2 bits chessboard (BitBoards) with the computer storage capacity substantially higher. The board said the demand for space is not often designers most concern.
Date : 2008-10-13 Size : 1.77mb User : sdaf
[Other resource] JOS DL : 0: mean-shift跟踪算法中核窗口大小的自动选区
Date : 2008-10-13 Size : 525.74kb User : 阿亚拉
[Other resource] BCFO DL : 0: We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation, phase-shift keying, and pulse amplitude modulation communications systems.We study the performance of a standard CFO estimate, which consists of first raising the received signal to the Mth power, where M is an integer depending on the type and size of the symbol constellation, and then applying the nonlinear least squares (NLLS) estimation approach. At low signal-to noise ratio (SNR), the NLLS method fails to provide an accurate CFO estimate because of the presence of outliers. In this letter, we derive an approximate closed-form expression for the outlier probability. This enables us to predict the mean-square error (MSE) on CFO estimation for all SNR values. For a given SNR, the new results also give insight into the minimum number of samples required in the CFO estimation procedure, in order to ensure that the MSE on estimation is not significantly affected by the outliers.
Date : 2008-10-13 Size : 1.21mb User : 吴大亨
[Other resource] work3 DL : 0: 對於bmp影像做銳利化區塊化並且採用mean-shift作法
Date : 2008-10-13 Size : 1.38mb User : 義安
[Other resource] Mean-shift DL : 0: 学习meanshift跟踪算法的好程序，值得搞图像序列目标跟踪的人研究
Date : 2008-10-13 Size : 124.86kb User : fjun
[Other resource] AnIntroductiontoMeanShift DL : 0: 均值漂移算法的详细介绍，论证均值漂移算法的收敛性，介绍mean-shift算法在图像分割，目标跟踪领域的应用
Date : 2008-10-13 Size : 1.47mb User : william
[Other resource] ms_segmenter DL : 0: mean shift
Date : 2008-10-13 Size : 36.55kb User : keroppi