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Kohonen's Self Organizing Maps in C++ with Application in Computer Vision Area

, 20 Nov 2007
The article demonstrates the self organizing maps clustering approach for unsupervised AI classification tasks with application examples in computer vision area for faces clustering and recognition
som_demo.zip
bin
rgb.som
rgb_1.som
som.exe
som_src.zip
src
Lib
LibSOM
#pragma once



class CSignal
{

        int format;

        HANDLE fp, fpmap;
        LPVOID lpMap;


        bool read11(wchar_t *fname);           //obsolete
        //void read12(wchar_t *fname);         //obsolete
        bool read13(wchar_t *fname);

        void changeext(wchar_t *path, wchar_t *ext);


public:
        CSignal(wchar_t *fname);                  //open existing file
        CSignal(wchar_t *fname, int n, int m);    //create new
        ~CSignal();


        int N, M;                             //NxM size of mapped array
        vector<float *> data;                 //N array of pointers to filemapping
        wchar_t name[_MAX_PATH];              //file name


        void dump(wchar_t *fname);            //dump contents to text file

        void minmax(float *buff, int len, float &min, float &max);
        void nminmax(float *buff, int len, float a, float b);
        void nenergy(float *buff, int len, int L = 2);


};



/*
    reads data from list file

	1.      file1  1
                file2  2
		file3  1
		....

     files in separate files on disk    1.1 - simple text file
	                                1.2 - ecg like data (header in this file)
				        1.3 - mitbih like format (header in separate file *.hea  [N M])


    AI file format
    2.          file1  1
	        x1 x2 x3 ... xn
		file2  2
		x1 x2 x3 ... xn
		file3  1
		x1 x2 x3 ... xn
		...

     files data in this list file

*/

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License

This article, along with any associated source code and files, is licensed under The GNU General Public License (GPLv3)

About the Author

Chesnokov Yuriy
Engineer
Russian Federation Russian Federation
No Biography provided

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