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1)  direct supervised locality preserving projections (DSLPP)
直接监督保局投影
2)  supervised locality preserving projections (SLPP)
监督保局投影
3)  supervised locality-preserving projections
有监督保局投影
1.
New supervised locality-preserving projections algorithm for face recognition
一种新的有监督保局投影人脸识别算法
4)  Supervised Locality Preserving Projection (SLPP)
监督局部保留投影
1.
Supervised Locality Preserving Projection (SLPP) is a generalization of Locality Preserving Projection (LPP) in the case of supervised learning.
针对监督的局部保留投影算法(Supervised Locality Preserving Projection,SLPP)在小样本情况下矩阵的奇异性问题,该文提出了一种广义的监督局部保留投影算法(Generalized Supervised Locality Preserving Projection,GSLPP)。
5)  locality preserving projections(LPP)
保局投影
1.
Firstly,face images are mapped into low-dimensional manifold subspace using Locality Preserving Projections(LPP).
首先,运用保局投影将图像投影到低维的表情流形子空间,再在流形子空间里对它们进行高阶奇异值分解,最后在个人子空间和表情子空间里完成人脸和表情识别。
6)  LPP
保局投影
1.
Locality Preserving Projections (LPP) is based on a nearest neighbor graph which models the local geometrical structure of the image manifold.
保局投影算法的基础是构造一个模拟图像局部结构的最近相邻图,但该最近相邻图并不总能够准确表示图像的流形结构,该文提出了一种基于保局投影的迭代保局投影优化算法。
2.
A Random Sampling Subspace Locality Preserving Projection(RSSLPP) method is proposed to improve the recognition performance of a single Locality Preserving Projection(LPP).
针对单一保局投影(LPP)算法分类识别能力弱的问题,提出了一种随机采样子空间保局投影算法(RSSLPP)。
3.
In view of the problems of feature extraction in face recognition, a new face image feature extraction and recognition method—Gabor Discriminant Locality Preserving Projections (GDLPP) is proposed in this paper.
针对人脸识别中的特征提取问题,本文提出了一种结合Gabor小波特征和判别保局投影的人脸识别算法—GDLPP。
补充资料:直接
不经过中间事物的。与“间接”相对:直接取用|直接关系。
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