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compare_pcl_gpucpu-master
对比CPU和GPU加速,pcl::cuda的使用教程,利用随机采样一致(RANSAC)去除地平面等例子。(Compare CPU and GPU acceleration, pcl::cuda tutorial, using random sampling consistency (RANSAC) to remove ground plane and other examples.)
- 2021-02-28 20:49:36下载
- 积分:1
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seisplot
SEISPLOT 可以弥补FIMAGE软件带来的不足,即可以实时地显示更多剖面。而且还可以进行其它格式的转换。(seisplot is a software for seismic profile viewing.)
- 2010-06-06 17:30:10下载
- 积分:1
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Axisch
各个坐标系之间的坐标变化:地心大地坐标到地心空间大地直角系,地心系和测站系,测站系和测站系等之间的变化,旋转,平移。(Coordinate changes between the various coordinate systems: geocentric geodetic coordinate system to the geocentric Cartesian space earth, geocentric system and station lines, change the station, such as lines and lines between stations, rotation, translation)
- 2013-12-31 23:31:40下载
- 积分:1
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efficient_subpixel_registration
一种精确地二维图像配准方法,实现亚像素的配准。(An accurate two-dimensional image registration method to achieve sub-pixel registration.)
- 2017-10-28 10:08:59下载
- 积分:1
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GMMP-and-tracking
活动目标检测源码,用混合高斯算法编写,适用于复杂场景视频监控(alive target detection,used in GMM algorithm)
- 2014-02-22 16:00:59下载
- 积分:1
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Floyd-Steinberg
利用误差扩散算法中的Floyd-Steinberg抖动算法来对图像进行二值化处理,从而方便图像调频加网输出(The use of error diffusion algorithm of Floyd-Steinberg dithering algorithm to image binarization treatment, thus facilitating image output FM Screening)
- 2021-04-08 21:39:00下载
- 积分:1
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gridreciprial
梯度倒系数实现背景抑制,提高小目标检测的信噪比(reversing Coefficients gradient background suppression, and enhance the signal-to-noise ratio target detection)
- 2007-01-19 11:50:43下载
- 积分:1
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mnist_uint8
压缩文件是CNN卷积神经网络图像处理的数据库mnist_uint8.mat(Compressed file is the database of CNN convolution neural network image processing mnist_uint8.mat)
- 2020-12-08 19:49:19下载
- 积分:1
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ImageRecuperate
4_1:生成模糊化实验图像
4_2:维纳滤波复原
4_3:约束最小二乘滤波复原
4_4:Lucy-Richardson滤波复原
4_5:盲卷积滤波复原(4_1: generate fuzzy images of experimental 4_2: 4_3 restoration Wiener filtering: constrained least squares filtering recovery 4_4: Lucy-Richardson filter recovery 4_5: Blind deconvolution filter to recover)
- 2020-07-03 04:00:01下载
- 积分:1
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MyBayes
2.编写两类正态分布模式的贝叶斯分类程序。
设以下模式类别具有正态概率密度函数:
ω1:{(0 0)T, (2 0)T, (2 2)T, (0 2)T}
ω2:{(4 4)T, (6 4)T, (6 6)T, (4 6)T}
(1)设P(ω1)= P(ω2)=1/2,求这两类模式之间的贝叶斯判别界面的方程式。
(2)绘出判别界面。
3.已知服从正态分布的两类训练样本集分别为
:,,,,
:,,,
,试问属于哪一类?
4.设有两类一维模式,每一类都是正态分布,两类的均值和均方差分别为,;,。
采用(0-1)损失函数,且。
(1)试绘出两类模式的密度函数曲线,其判别界面位于何处?
(2)若已获得样本:-3,-2,1,3,5,试判断它们各属于哪一类。(bayes ,matlab)
- 2013-04-12 09:34:26下载
- 积分:1