1)mean shift均值漂移
1.Non-linear scale space filtering based on mean shift;基于均值漂移的非线性尺度空间滤波
2.IR target tracking based on mean shift and particle filter;基于均值漂移和粒子滤波的红外目标跟踪
3.Mean shift research and applications;均值漂移算法的研究与应用
英文短句/例句
1.KNN-based mean shift algorithm for image segmentation基于KNN的均值漂移图像分割算法
2.Research On the SAR Images Segmentation Algorithm Based On Mean Shift基于均值漂移的SAR图像分割方法研究
3.A mean-shift algorithm based on pretreatment一种基于优化预处理的均值漂移算法
4.A Very Fast Adaptive Mean Shift Clustering Method一种快速自适应的均值漂移聚类算法
5.The Applicantion of Mean Shift Object Tracking Algorithm in Video Sequences均值漂移算法在视频目标跟踪中的应用
6.An improved mean shift algorithm applied to medical ultrasound images segmentation基于均值漂移的医学超声图像分割改进算法
7.Mean Shift Paticle Filter Based Methods for Target Tracking基于均值漂移粒子滤波的目标跟踪算法研究
8.Image segmentation of mean shift based on improved 2D histogram一种改进的二维直方图均值漂移分割算法
9.Color image segmentation based on mean shift and multi-feature fusion融合多特征的均值漂移彩色图像分割方法
10.Color image segmentation method combining mean shift and region merging融合均值漂移和区域合并的彩色图像分割方法
11.Study on Target Model Update Method in Mean Shift Algorithm均值漂移算法中的目标模型更新方法研究
12.Background subtraction and extend mean shift algorithm for object tracking基于背景提取和扩展均值漂移算法的目标跟踪
13.A Method of small target detection in IR image based on morphological filter and Mean Shift algorithm基于形态滤波和均值漂移红外小目标检测方法
14.Mobile Node Localization Based on Mean Shift and Joint Particle Filter in Wireless Sensor Networks基于均值漂移和联合粒子滤波的移动节点定位算法
15.Implementation of multi-scales segmentation for high resolution RS images based on cluster均值漂移高分辨率遥感影像多尺度分割的集群实现
16.CT metal artifact correction based on Mean-Shift segmentation基于均值漂移图像分割技术去除CT图像金属伪影
17.Correlation Test for Mean-shift Model with AR(1) Errors具有AR(1)误差的均值漂移模型的Score检验和似然比检验
18.Improved CONDENSATION Face Tracking Algorithm Based on Mean-shift Drift基于均值移动确定性漂移的改进CONDENSATION人脸跟踪
相关短句/例句
mean-shift均值漂移
1.A point model simplified method based on mean-shift clustering;基于均值漂移聚类的点模型简化方法
2.Object tracking based on particle filter and mean-shift;基于粒子滤波和均值漂移的目标跟踪
3.Dual template algorithm for Mean-Shift template update均值漂移跟踪的双模板更新算法
3)fast mean shift快速均值漂移
1.Original contours of the level set method are obtained by pre-segmentation of the fast mean shift method to decrease iteration times of the level set function.同时,利用快速均值漂移法对图像进行预分割,将得到的轮廓作为水平集方法的初始轮廓,从而降低水平集函数的迭代次数。
2.Combined with fast mean shift algorithm presented by Zhang [4],a new segmentation method for MR images based on level set is then proposed.本文针对脑部 MR 图像具有弱边缘、对比度低等特点,对 Chunming Li 在[3]中提出的水平集方法(li 方法)进行了改进,并且结合 Kai Zhang 等人在[4]中提出的快速均值漂移算法(Fast Mean Shift)提出了一种新的 MR 图像分割算法。
4)mean shift algorithm均值漂移算法
1.Adaptive human face tracking based on mean shift algorithm;基于均值漂移算法的人脸自适应跟踪
2.In order to localize the mobile sensor nodes in real time and with high accuracy,by employing mean shift algorithm to generate the proposal distribution for the joint particle filter,a novel mobile node localization algorithm is proposed,which we called Mean Shift Particle Filter.针对无线传感器网络移动节点定位面临的高精度和实时性要求,把均值漂移算法引入联合粒子滤波(Joint ParticleFilter)框架,提出了基于均值漂移和联合粒子滤波的移动节点定位算法。
5)mean-shift algorithm均值漂移算法
1.Firstly pictures of the fabric were taken and the images were rectified, and then K-mean cluster algorithm, threshold algorithm and mean-shift algorithm were used to implement automatic color clustering and segmentation of the pattern images by programming of Visual C++.首先对织物的实拍图进行必要的矫正,接着采用K-均值聚类算法、阈值分割算法、均值漂移算法以及编程工具VisualC++,进行色彩的聚类和分割,实现了织物图像彩色花型的自动识别,最后在均值漂移算法的基础上,在取定的图像范围内自动生成了彩色意匠图。
2.It creatively applies mean-shift algorithm which.本文的目标就是把对纬编提花针织物图像的识别从灰度级别上升到真彩级别，并且开创性地把基于模式识别上常用的均值漂移算法运用到对纬编提花针织物图像的自动分割上来。
6)mean shift outlier model均值漂移模型
1.Based on the Bayes framework,it is proved that the estimates of the case deletion model(CDM) and the mean shift outlier model(MSOM) are not necessary equal in a wide class of statistical models whenγ,the shift parameter,has informative priority.文中证明了在Balyes框架下,当漂移参数γ服从有信息先验时,在相当广泛的统计模型中,数据删除模型(CDM)和均值漂移模型(MSOM)的参数估计不相等,几个数值例子验证了相应的结论。
2.And we show that the case deletion model i s equivalent to mean shift outlier model.本文讨论了这种模型中未知参数具有正态先验分布时的参数Bayes估计方法,并对这种估计进行了影响分析,证明了删除模型与均值漂移模型中参数的Bayes估计相同,利用Cook统计量给出了删除模型下参数的Bayes估计的影响度量。
延伸阅读
均值不等式几个重要不等式(一)一、平均值不等式设a1,a2,…, an是n个正实数，则，当且仅当a1=a2=…=an时取等号1.二维平均值不等式的变形(1)对实数a,b有a2+b2³2ab (2)对正实数a,b有(3)对b>0，有， (4)对ab2>0有，(5)对实数a,b有a(a-b)³b(a-b) (6)对a>0,有(7) 对a>0,有 (8)对实数a，b有a2³2ab-b2(9) 对实数a，b及l¹0，有二、例题选讲例1.证明柯西不等式证明：法一、若或命题显然成立，对¹0且¹0，取代入(9)得有两边平方得法二、，即二次式不等式恒成立则判别式例2.已知a>0,b>0,c>0,abc=1,试证明：(1)(2)证明：(1)左=[]=³(2)由知同理：相加得：左³例3.求证：证明：法一、取，有a1(a1-b)³b(a1-b), a2(a2-b)³b(a2-b),…, an(an-b)³b(an-b)相加得(a12+ a22+…+ an2)-( a1+ a2+…+ an)b³b[(a1+ a2+…+ an)-nb]³0所以法二、由柯西不等式得： (a1+ a2+…+ an)2=((a1×1+ a2×1+…+ an×1)2£(a12+ a22+…+ an2)(12+12+…+12)=(a12+ a22+…+ an2)n,所以原不等式成立例4.已知a1, a2,…,an是正实数，且a1+ a2+…+ an<1，证明：证明：设1-(a1+ a2+…+ an)=an+1>0,则原不等式即nn+1a1a2…an+1£(1-a1)(1-a2)…(1-an)1-a1=a2+a3+…+an+1³n1-a2=a1+a3+…+an+1³n…………………………………………1-an+1=a1+a1+…+an³n相乘得(1-a1)(1-a2)…(1-an)³nn+1例5.对于正整数n，求证：证明：法一、>法二、左==例6.已知a1,a2,a3,…,an为正数，且，求证：(1)(2)证明：(1)相乘左边³=(n2+1)n证明(2)左边= -n+2(= -n+2×[(2-a1)+(2-a2)+…+(2-an)](³ -n+2×n
