搜索资源列表
20054179
- 包括Polygonal Approximations,Signatures,The Skeleton of a Region-including Bayesian, Signatures, The Skeleton of a Region
GLRAM
- 算法实现:Jieping Ye. Generalized low rank approximations of matrices. Machine Learning, Vol. 61, pp. 167-191, 2005. -Algorithm : Jieping Ye. Generalized low rank approximatio ns of matrices. Machine Learning, Vol. 61. pp. 16
surface~simplification~using~quadric~error~metrics
- Many applications in computer graphics require complex, highly detailed models. However, the level of detail actually necessary may vary considerably. To control processing time, it is often desirable to use approx
match-v3.3.src
- This software implements stereo algorithms described in the following papers: Vladimir Kolmogorov and Ramin Zabih \"Multi-Camera scene Reconstruction via Graph Cuts\" In: European Conference on Computer Vi
sldemo_f14
- This demonstration models a flight control for the longitudinal motion of a Grumman Aerospace F-14 Tomcat. First order linear approximations of the aircraft and actuator behavior are connected to an analog flight cont
approx_coars
- Coarsening approximations of belief functions
computing dense correspondence graph cuts
- computing dense correspondence # # (disparity map) between two images using graph cuts This software implements stereo algorithms described in the following papers: Vladimir Kolmogorov and Ramin Zabih
fast Gaussian process latent variable model
- fast Gaussian process latent variable model Software (FGPLVM). This toolbox allows for larger GP-LVM models through using the sparse approximations suggested in papers by authors including Titsias, Snelson, Ghahramani,
20054179
- 包括Polygonal Approximations,Signatures,The Skeleton of a Region-including Bayesian, Signatures, The Skeleton of a Region
GLRAM
- 算法实现:Jieping Ye. Generalized low rank approximations of matrices. Machine Learning, Vol. 61, pp. 167-191, 2005. -Algorithm : Jieping Ye. Generalized low rank approximatio ns of matrices. Machine Learning, Vol. 61. pp. 16
surface~simplification~using~quadric~error~metrics
- Many applications in computer graphics require complex, highly detailed models. However, the level of detail actually necessary may vary considerably. To control processing time, it is often desirable to use approx
match-v3.3.src
- This software implements stereo algorithms described in the following papers: Vladimir Kolmogorov and Ramin Zabih "Multi-Camera scene Reconstruction via Graph Cuts" In: European Conference on Computer Visi
sldemo_f14
- This demonstration models a flight control for the longitudinal motion of a Grumman Aerospace F-14 Tomcat. First order linear approximations of the aircraft and actuator behavior are connected to an analog flight cont
approx_coars
- Coarsening approximations of belief functions
pca
- pca: The enclosed function PCA implements what is probably the method of choice for computing principal component analyses fairly efficiently, while guaranteeing nearly optimal accuracy. The enclosed function DIFFSNORM p
sparsify_0_3
- sparsify is a set of Matlab m-files implementing a range of different algorithms to calculate sparse signal approximations. Currently sparsify contains two main sets of algorithms, greedy methods (collected under the nam
0707.1315v1
- We analyze, both analytically and numerically, the effectiveness of cloaking an infinite cylinder from observations by electromagnetic waves in three dimensions. We show that, as truncated approximations of the ide
IDA
- 对两幅图像特征点对匹配算法的一个实现，采用了09年pami一文章的观点，算法名称IDA(Incremental Dissimilarity Approximations)-Feature points of two images of an implementation of matching algorithm used pami a 2009 article, views, the algorithm name of IDA (In
IDAc
- 对两幅图像特征点对匹配算法的一个实现，采用了09年pami一文章的观点，算法名称IDA(Incremental Dissimilarity Approximations)，C语言实现版本-Feature points of two images of an implementation of matching algorithm used pami a 2009 article, views, the algorithm name of
ALG024
- SECANT法求解一个连续方程，f(x) = 0，给两个初始值- SECANT ALGORITHM 2.4 To find a solution to the equation f(x) = 0 given initial approximations p0 and p1: INPUT: initial approximation p0, p1 tolerance TOL