Description: Watermarking embeds information into a digital signal like
audio, image, or video. Reversible image watermarking can restore the
original image without any distortion after the hidden data is extracted.
In this paper, we present a novel reversible watermarking scheme using
an interpolation technique, which can embed a large amount of covert
data into images with imperceptible modification. Different from previous
watermarking schemes, we utilize the interpolation-error, the difference
between interpolation value and corresponding pixel value Platform: |
Size: 225280 |
Author:isclor |
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Description: 关于metric learning的综述，涉及到许多的知识：SVM、kernel、SDP等-This paper surveys the field of distance
metric learning from a principle perspective, and includes a broad selection of recent work. In particular, distance metric learning is reviewed under different
learning conditions: supervised learning versus unsupervised learning, learning in a global sense versus in a local sense and the distance matrix based on linear kernel versus nonlinear kernel. In addition, this paper discusses a number of techniques
that is central to distance metric learning, including convex programming, positive semi-definite programming, kernel learning, dimension reduction, K Nearest Neighbor, large margin classification, and graph-based approaches. Platform: |
Size: 322560 |
Author:刘建飞 |
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Description: 基于L1范数稀疏距离测度学习的单类分类算法Based on the L1 norm of sparse distance metric learning one class classification algorithm-Based on the L1 norm of sparse distance metric learning one class classification algorithm Platform: |
Size: 480256 |
Author:na989 |
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Description: 5.采用概率密度比值估计的距离度量学习.rar-5.Probability density ratio is estimated using a distance metric learning.rar Platform: |
Size: 1268736 |
Author:wang |
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Description: 关于度量学习的一篇经典文章，利用度量学习提高KNN的分类正确率，如果对度量学习有兴趣，这篇是必读的文章-Metric learning about a classic article, the use of metrics to improve learning KNN classification accuracy, if you are interested to measure learning, this is a must read article Platform: |
Size: 1084416 |
Author:涛 |
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Description: 根据样本信息利用方式的不同, 将其划分成基于成对约束和非成对约束的距离度量学习算法,-According to the sample information. By the way, will be divided into pairwise constraints and non pairwise constraint based distance metric learning algorithms, Platform: |
Size: 710656 |
Author:贺俊 |
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Description: SOM神经网路和DML的结合，CVPR2014文章仿真，保证分类器的Discriminative特性和SOM快速匹配特性！-the combination of the SOM neural network and the distance metric learning method Platform: |
Size: 14336 |
Author:loo |
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Description: 基于马氏距离度量的局部线性嵌入算法
局部线性嵌入算法(LLE)中常用欧氏距离度量样本间相似度.而 对于图像等高维数据,欧氏距离不能准确体现样本间的相似程度.文中提出基于马氏距离度量的局部线性嵌入算法(MLLE).算法首先从现有样本中学习到一个 马氏度量,然后在LLE算法的近邻选择、现有样本及新样本降维过程中用马氏度量作为相似性度量.将MLLE算法及其它典型的流形学习算法在ORL和 USPS数据库上进行对比实验,结果表明MLLE算法具有良好的识别性能.
-Based on local linear embedding algorithm Mahalanobis distance metric LLE algorithm (LLE) common Euclidean distance measure of similarity between the samples. For high-dimensional image data, Euclidean distance can not accurately reflect the degree of similarity between samples. In this paper, Mahalanobis distance metric based on local linear embedding algorithm (MLLE). Firstly, learning the existing sample to a Markov measure, then LLE neighbor algorithm selection, existing samples and new samples dimensionality reduction process using Markov measure as a similarity measure would MLLE algorithms and other typical manifold learning algorithm on ORL and USPS to compare experimental results show MLLE algorithm has good recognition performance. Platform: |
Size: 406528 |
Author:fangsm |
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Search - distance metric learning