000			02112naa2a2200241 4500
001			167841
005			20231029193404.0
035			_a(RuTPU)RU\TPU\book\182089
090			_a167841
100			_a20091021d2001 k y0rusy50 ca
101	0		_arus
102			_aRU
200	1		_aThe neuronet technology for aerospace monitoring datainterpretation _fN. G. Markov, A.A. Napryushkin, D.G. Badmaev
330			_aFor solving many practically important problems of ecology and landscape studying the information obtained by remote sensing (RS) methods plays an increasing role. Nowadays the development of high-automated methods and means of processing and interpretation of RS data is an extremely urgent problem. In the situations of training information lack and considerable uncertainty the most efficient approach for solving problems of RS data interpretation is application of neuronet algorithms of recognition of objects on images without training. The authors propose a neuronet technology for interpretation of aerospace monitoring data with the use of Kohonen's algorithm, based on a concept of dynamic kernels. The description of the proposed neuronet technology is given, particularities of its implementation are considered, and first results of application of the technology for solving problems of forest type mapping and assessing the pollution of reservoirs in the Tomsk region are shown.
461		1	_0(RuTPU)RU\TPU\book\39044 _tKorus 2001 _oThe 5th Korea-Russia International Symposium on Science and Technology _oJune 26 - July 3, 2001, Tomsk _fТомский политехнический университет ; KORUS _d2001-
463		0	_0(RuTPU)RU\TPU\book\31152 _y0-7803-7008-2 _tVol. 1 _vP. 88-91 _d2001 _p392 p.
610	1		_aтруды учёных ТПУ
700		1	_aMarkov _bN. G. _cDoctor of Engineering, Professor of TPU _cRussian specialist in Informatics and Computing _f1950- _gNikolai Grigorevich _2stltpush _3(RuTPU)RU\TPU\pers\24811
701		1	_aNapryushkin _bA.A. _4070
701		1	_aBadmaev _bD.G. _4070
801		1	_aRU _b63413507 _c20091021
801		2	_aRU _b63413507 _c20120118 _gRCR
942			_cBK