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Saliency_Detection
说明： 简单可用的显著性检测程序，用matlab'语言实现，经调试可用。(A matlab code for Saliency Detection)
- 2017-07-30 17:36:58下载
- 积分：1
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read_txt
IDL读取txt，txt第一列是纬度，第二列是经度，第三列是DN值， 坐标转行列号 ，并以图像的形式输出(IDL reads TXT. The first column of TXT is latitude, the second column is longitude, and the third column is DN value. The coordinate turns the line and column number and outputs it in the form of image)
- 2019-04-18 10:01:30下载
- 积分：1
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WaterShed
WaterShed图像分割方法，使用C++来编写的程序，分割效果还不错，不过要用的话，自己还是要调一下的。(WaterShed image segmentation method, using C++ to write programs, segmentation results were pretty good, but use the words that he is still would like to stress the.)
- 2010-03-13 14:03:35下载
- 积分：1
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matlab_GUI_showing
本例程通过matlab编写，显示一个GUI。在GUI中将输入到程序中的数据进行绘图。本例程能够实时进行绘图，并且可以将数据进行显示。同时还可以将输入到程序中的数据进行保存。在GUI中设置有控制开关，能够通过点击开关，将数据保存在不同的文本中便于后续处理使用。(This routine is written by matlab and displays a GUI. The data input into the program is drawn in the GUI. This routine can be plotted in real time and data can be displayed. At the same time, the data input into the program can also be saved. A control switch is set in the GUI, and the data can be saved in different texts by clicking the switch to facilitate subsequent processing.)
- 2018-06-06 19:31:09下载
- 积分：1
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ImageDenoisingKSVD-master
采用K-SVD对图像进行去噪处理。可以对不同类型的图像进行去噪处理。(Image denoising using K-SVD)
- 2019-06-06 19:56:25下载
- 积分：1
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structure-elemdnt-analysis
Space structure with static analysis % elastic beam element space structure with static analysis, elastic beam element
- 2017-08-14 15:59:30下载
- 积分：1
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PCA
主成分分析 （ Principal Component Analysis ， PCA ）或者主元分析。是一种掌握事物主要矛盾的统计分析方法，它可以从多元事物中解析出主要影响因素，揭示事物的本质，简化复杂的问题。计算主成分的目的是将高维数据投影到较低维空间。给定 n 个变量的 m 个观察值，形成一个 n ′ m 的数据矩阵， n 通常比较大。对于一个由多个变量描述的复杂事物，人们难以认识，那么是否可以抓住事物主要方面进行重点分析呢？如果事物的主要方面刚好体现在几个主要变量上，我们只需要将这几个变量分离出来，进行详细分析。但是，在一般情况下，并不能直接找出这样的关键变量。这时我们可以用原有变量的线性组合来表示事物的主要方面， PCA 就是这样一种分析方法。(Principal component analysis (Principal Component Analysis, PCA) or PCA. Is a statistical method to grasp the principal contradiction of things, it can be resolved diverse things out the main factors, revealing the essence of things, simplifying complex problems. The purpose of calculating the main component of high-dimensional data is projected to a lower dimensional space. Given n variables of m observations, forming an n ' m of the data matrix, n is usually large. For a complex matters described by several variables, it is difficult to know, so if you can grab something to focus on key aspects of analysis? If the main aspects of things just reflected on several key variables, we only need to separate out these few variables, for detailed analysis. However, in general, does not directly identify this critical variables. Then we can represent the major aspects of things with a linear combination of the original variables, PCA is one such analysis.)
- 2021-01-28 21:48:40下载
- 积分：1
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HDMI-Type-A、B、C、D接口图
说明： HDMI接口定义，包括a，b，c，d，包括各种接口的详细介绍(HDMI interface definition, including a, b, c, d, including detailed introduction of various interfaces)
- 2020-06-17 03:40:01下载
- 积分：1
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SFCM
说明： 基于空间信息的模糊均值聚类算法，SFCM，适用于数据分析，图像分割(space fuzzy-c-means clustering algorithm)
- 2021-04-22 21:08:48下载
- 积分：1
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sar
一幅含有噪声的SAR 图像,可用于道路检测,或者图像去噪的研究.图像内容相对丰富清晰.(A SAR image with noise, can be used for road detection, or image denoising studies. Relative abundance of clear image content.)
- 2009-05-25 14:23:05下载
- 积分：1
