The neuronet technology for aerospace monitoring datainterpretation; Korus 2001; Vol. 1

The neuronet technology for aerospace monitoring datainterpretation; Korus 2001; Vol. 1

Bibliographic Details
Parent link:Korus 2001: The 5th Korea-Russia International Symposium on Science and Technology/ Томский политехнический университет ; KORUS.— , 2001-
Vol. 1.— 2001.— P. 88-91
Main Author: Markov N. G. Nikolai Grigorevich
Other Authors: Napryushkin A.A., Badmaev D.G.
Summary:For 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.
Language:Russian
Published: 2001
Subjects:
труды учёных ТПУ
Format: Book Chapter
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=167841

MARC

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200 1 |a The neuronet technology for aerospace monitoring datainterpretation  |f N. G. Markov, A.A. Napryushkin, D.G. Badmaev 
330 |a For 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  |t Korus 2001  |o The 5th Korea-Russia International Symposium on Science and Technology  |o June 26 - July 3, 2001, Tomsk  |f Томский политехнический университет ; KORUS  |d 2001-  
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701 1 |a Badmaev  |b D.G.  |4 070 
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