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Precision_Recall_F1-Measure
信息检索和自然语言处理中经常会使用这些参数:准确率（Precision）、召回率（Recall）以及综合评价指标（F1-Measure ） (These parameters are often used in information retri and natural language processing (Precision), recall rate (Recall), and comprehensive uation index (F1-Measure).
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- 2015-12-09 10:49:57下载
- 积分：1
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11
说明： LSA的第一步是要去创建词到标题（文档）的矩阵。在这个矩阵里，每一个索引词占据了一行，每一个标题占据一列。每一个单元（cell）包含了这个词出现在那个标题中的次数。例如，词”book”出现在T3中一次，出现在T4中一次，而”investing”在所有标题中都出现了一次。一般来说，在LSA中的矩阵会非常大而且会非常稀疏（大部分的单元都是0）。这是因为每个标题或者文档一般只包含所有词汇的一小部分。更复杂的LSA算法会利用这种稀疏性去改善空间和时间复杂度。(The Little Book of Common SenseInvesting: The Only Way to Guarantee Your Fair Share of StockMarket Returns ,)
- 2015-12-23 20:26:03下载
- 积分：1
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noise
图片去噪：对一幅图像加入不同的噪声（随机点噪声、椒盐噪声等），选取不同的方法去噪，比如说邻域平均、中值滤波、图像迭加等，比较对于不同的噪声，不同的方法哪种更好(Image denoising: for an image by adding different noise (random-dot noise, salt and pepper noise, etc.), select a different method of denoising, for example, the neighborhood average, median filter, image superposition and so on, compared for different noise, different methods which better)
- 2007-11-08 21:00:13下载
- 积分：1
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GaborTexture
使用MFC以及Gabor小波处理进行图像的特征纹理提取(Using MFC and Gabor wavelet to extract texture features for image)
- 2011-10-07 08:46:32下载
- 积分：1
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SaliencyToolbox
ITTI视觉显著性检测MATLAB工具箱可用于检测图像视觉显著性(ITTI visual saliency detection MATLAB toolbox can be used to detect visual saliency of images)
- 2020-11-06 20:49:50下载
- 积分：1
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bestlinefusion
最佳拼接线方法进行图像拼接，对学习图像拼接很有用处(The best method of splicing line image mosaic, image stitching is useful for learning)
- 2020-06-30 01:40:02下载
- 积分：1
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灰度共生矩阵
说明： 获取图像灰度共生矩阵特征值代码，包括能量、熵、惯性矩和相关度的均值和标准差，已测试，代码及注释清晰。(The eigenvalue codes of gray level co-occurrence matrix, including the mean and standard deviation of energy, entropy, moment of inertia and correlation, have been tested and the codes and annotations are clear.)
- 2020-06-25 04:20:02下载
- 积分：1
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Image-Matching
主要介绍关于图像匹配的相应matlab程序设计(Focuses on the appropriate image matching matlab program )
- 2013-11-09 11:34:55下载
- 积分：1
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GMM高斯混合模型进行背景建模（Matlab）
转：https://blog.csdn.net/jinshengtao/article/details/26278725
混合高斯背景建模是基于像素样本统计信息的背景表示方法，利用像素在较长时间内大量样本值的概率密度等统计信息(如模式数量、每个模式的均值和标准差)表示背景，然后使用统计差分(如3σ原则)进行目标像素判断，可以对复杂动态背景进行建模，计算量较大。
在混合高斯背景模型中，认为像素之间的颜色信息互不相关，对各像素点的处理都是相互独立的。对于视频图像中的每一个像素点，其值在序列图像中的变化可看作是不断产生像素值的随机过程，即用高斯分布来描述每个像素点的颜色呈现规律单模态(单峰)，多模态(多峰)(Gaussian mixture background modeling is a background representation method based on the statistical information of pixel samples. Statistical information such as the number of patterns, the mean and standard deviation of each pattern are used to represent the background. Statistical difference (such as 3_principle) is used to judge the target pixel. Complex dynamic background modeling has a large amount of computation.
In the Gaussian mixture background model, it is considered that the color information between pixels is uncorrelated and the processing of each pixel is independent of each other. For each pixel in a video image, the change of its value in a sequential image can be seen as a random process that produces pixel values continuously, i.e. Gaussian distribution is used to describe the regularity of color rendering of each pixel in single mode (single peak) and multi-mode (multi-peak).)
- 2020-11-01 09:49:54下载
- 积分：1
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narrowband
说明： 水平集图像分割方法中的窄带技术的MATLAB代码实现(Level set image segmentation methods narrowband technology MATLAB code)
- 2008-10-02 10:04:49下载
- 积分：1
