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Visual C++ (VC++)]
ART.rar
ART neural network with the input of Chinese characters to identify the classification of the letters that have memory as well as with similar letters to the correct identification of noise of new letters and the letters too much noise can automatically ...
Category:
AI-NN-PR Upload User:
mingkee301 Size:
91K
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Matlab]
KPMtools.rar
Matlab toolkit added fat count, including all kinds of noise code and filter code, such as backward Smoother
Category:
matlab Upload User:
xingchq Size:
217K
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Matlab]
ohspeci.rar
An indirect estimate of the signal spectrum of 1.5-dimensional method, 1.5-dimensional spectrum can effectively suppress Gaussian noise, to enhance low frequency components.
Category:
matlab Upload User:
atange Size:
1K
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Matlab]
lvbo.rar
Image filtering is generally used to eliminate the random noise, so the following procedure to add the typical noise, and then conduct various kinds of filter processing: mean filtering, median filtering, the minimum filtering, maximum filtering.
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Matlab]
jiazao.rar
Procedures add to the typical noise, Wiener filtering further recovery. For Wiener filtering, the graphics improved significantly. wiener2 function and deconvwnr functions are able to complete the function of Wiener filter, deconvwnr emphasis on image ...
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Visual C++ (VC++)]
datarecognization.rar
To achieve the number of gray-scale image recognition: includes 256 to gray image, binary, gradient sharpening to discrete noise, the overall tilt adjustment, character segmentation, size standards for normalization, tightening rearrangement, neural ...
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C/C++]
Gauss.rar
Consider Gaussian image wave can reduce the image noise. With a picture, in order to test
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C/C++]
Canny.rar
Of image edge detection. First, consider Gaussian wave images to reduce noise, and then for the image gradient, non-maximum suppression
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Visual C++ (VC++)]
denoise1.rar
Areas of source noise filtering algorithm, the input and output. Bin format source file, the suffix can also be removed, a word that is the bare data, float type. Can effectively suppress image noise