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segmeeeeeeeeeeeeeee.tar
- A general technique for the recovery of signi cant image features is presented. The technique is based on the mean shift algorithm, a simple nonparametric pro- cedure for estimating density gradients. Drawbacks of the current methods (includi
tree
- 二叉树的生成、查询、删除、插入等基本操作，及图像的动态显示-Tree generation, query, delete, insert the basic operation, and the image of dynamic display
ChildFrm
- The first scheme is based on the spatial locality of feature vectors corresponding to similar images. Learning is effected by modifying the query vector to incorporate the positive examples. The second scheme is based on “distorting” our view of
imgfeatures
- Similarly, during the query process, each quantized color in the query feature is searched separately to find matching image regions which contain that color. The results are then combined together so that image regions containing similar color
semisupervised_learning
- 包含8篇半监督学习方面的中文文献，关于半监督学习的中文文献并不是很多，我把我找到的一些文章贡献一下。分别为：“半监督学习综述”“有关半监督学习的问题及研究”“基于半监督学习的网络流量分析”“基于核策略的半监督学习方法”“一种基于半监督学习的多模态WEB查询精华方法”“半监督学习机制下的说话人辨认算法”“半监督学习在入侵系统中的应用”“基于半监督学习的眉毛图像分割方法”-Includes eight semi-supervised learning of Chinese literature on
TextQuery
- 文本查询程序，生成文本位置map，单词转换map。-Text query process, generate the text location map, the word conversion map.
goodimagequery
- 在本演示中，一个简单的图像检索方法，提出基于图像的颜色分布。用户只需提供一个“例子”的形象和搜索是基于这个例子（例如基于查询的图像）。包括图像和教学指令-In this demo, a simple image retrieval method is presented, based on the color distribution of the images. The user simply provides an "example" image and the search is base
Image retrieval
- 基于内容的图像查询，采用卷积神经网络，CNN代码使用了matconvnet工具包，包括代码和实验报告。(Content based image query, using convolutional neural networks, CNN code, using the matconvnet toolkit, including code and experimental reports.)