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A study of backscattered spectra dynamics of agricultural crops during growth period on the territory of the Krasnoyarskii Krai (Russia) / I. Yu. Pugacheva, A. F. Sid'ko, A. P. Shevyrnogov // Advances in Space Research. - 2010. - Vol. 45, Is. 10. - P1224-1230, DOI 10.1016/j.asr.2009.11.020 . - ISSN 0273-1177
Кл.слова (ненормированные):
Barley -- Oats -- Spectral brightness coefficients -- Spectral reflectance -- Wheat -- Agricultural crops -- Back-scattered -- Data base -- Ecological state -- Field ground -- Growth period -- Optical thickness -- Satellite data -- Seasonal dynamics -- Space image -- Spatial distribution -- Species composition -- Spectral brightness -- Spectral curves -- Spectral differences -- Spectral reflectances -- Underlying surface -- Reflection -- Size distribution -- Crops
Аннотация: The work presents the results of the study aimed at determining the seasonal dynamics of the spectral brightness and reflectance of agricultural crops (wheat, barley and oats) in the Krasnoyarskii Krai (Russia). The analysis of spectral curves obtained through field ground measurements and from satellite data showed that fine spectral differences can be used to study the spatial distribution of various types of vegetation and their ecological state. Based on the created electronic spectral brightness data base, the possibilities are shown of using spectrophotometric information for determining morphophysiological changes occurring in the plants and their species composition. The determined contrasts can be effectively used to obtain necessary information while processing space images, which suffer from natural interferences (varying optical thickness of the atmosphere, cloudiness, alterations in the scanner's angle of view, varying solar height, and highly inhomogeneous underlying surface). В© 2010 COSPAR.

Scopus
Держатели документа:
Institute of Biophysics, SB RAS, 50-50 Akademgorodok, Krasnoyarsk, Russian Federation : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Pugacheva, I.Yu.; Sid'ko, A.F.; Shevyrnogov, A.P.

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A study of spectral-polarization characteristics of plant canopies using land-based remote sensing / A. F. Sid'ko [et al.] // Journal of Quantitative Spectroscopy and Radiative Transfer. - 2013. - Vol. 129. - P109-117, DOI 10.1016/j.jqsrt.2013.06.001 . - ISSN 0022-4073
Кл.слова (ненормированные):
Farm crops -- Forest stands -- Spectral brightness coefficients -- Spectral-polarization characteristics -- Forest stand -- Near-infrared spectral regions -- Plant reflectance -- Polarized components -- Reflectance spectrum -- Reflection properties -- Spectral brightness -- Spectral-polarization characteristics -- Forestry -- Luminance -- Physiological models -- Polarization -- Reflection -- Crops -- brightness temperature -- canopy reflectance -- crop plant -- nadir -- polarization -- remote sensing -- spectral analysis -- Farm Crops -- Forestry -- Forests -- Polarization -- Reflection -- Triticum aestivum -- Zea mays
Аннотация: The study addresses reflection and spectral-polarization characteristics of forest stands and farm crops obtained under field conditions. The study of the reflection properties of farm crops shows that during the summer plant growing season, the major factors influencing the plant canopy reflectance are morpho-physiological parameters, plant architectonics, solar elevation h0, and viewing angle. The crop reflectance minimum was recorded at viewing angles 25-30В° with respect to the nadir. Coniferous and broadleaf forest stands had similar reflectance spectra of polarized light. The polarized component was smaller for all coniferous stands than for broadleaf ones. For broad-leaved farm crops (wheat and corn), the polarized component of the spectral brightness coefficients had a greater influence on the plant reflectance in the red and near-infrared spectral regions, ?>720nm. В© 2013 Elsevier Ltd.

Scopus
Держатели документа:
Institute of Biophysics of the Siberian Branch of RAS, 50-50 Akademgorodok, Krasnoyarsk, Russian Federation : 660036, Красноярск, Академгородок, д. 50, стр. 50

Доп.точки доступа:
Sid'ko, A.F.; Botvich, I.; Pisman, T.I.; Shevyrnogov, A.P.

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Analysis of the polarization characteristics of wheat and maize crops using land-based remote-sensing measurements / A. F. Sid’ko [et al.] // Biophysics. - 2015. - Vol. 60, Is. 4. - P668-671, DOI 10.1134/S0006350915040223 . - ISSN 0006-3509
Кл.слова (ненормированные):
crops -- optical remote sensing techniques -- polarization characteristics
Аннотация: This paper presents an analysis of the study of the polarized component of the reflectance factor (Rq) and the degree of polarization (P) of wheat and maize crops depending on the wavelength. The polarization characteristics were obtained in the field from an elevated work platform at heights of 10 to 18 m in June and July. Measurements were performed using a double-beam spectrophotometer with a polarized light filter attachment within the spectral range from 400 to 820 nm. The viewing angle was no greater than 20° with respect to the nadir. The reflection spectra of wheat and maize crops that were obtained using a polarizer adjusted to transmit the maximum and minimum amounts of light (Rmax and Rmin) were studied. Based on these reflection spectra, the polarization characteristics, which differ in the visible and infrared spectral regions, were determined and analyzed. © 2015, Pleiades Publishing, Inc.

Scopus
Держатели документа:
Institute of Biophysics, Siberian Branch, Russian Academy of Sciences, Akademgorodok 50/50, Krasnoyarsk, Russian Federation

Доп.точки доступа:
Sid’ko, A. F.; Botvich, I. Y.; Pisman, T. I.; Shevyrnogov, A. P.

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Neural networks playing 'matching pennies' with each other: Reproducibility of game dynamics / T. Dolgova, S. Bartsev // IOP Conference Series: Materials Science and Engineering : Institute of Physics Publishing, 2019. - Vol. 537: International Workshop on Advanced Technologies in Material Science, Mechanical and Automation Engineering - MIP: Engineering-2019 (4 April 2019 through 6 April 2019, ) Conference code: 149243, Is. 4, DOI 10.1088/1757-899X/537/4/042002
Кл.слова (ненормированные):
Condensed matter physics -- Engineering -- Industrial engineering -- Materials science -- Cognitive functions -- Dynamic patterns -- Essential features -- Meta strategies -- Neural correlates of consciousness -- Neuron excitation -- Qualitative differences -- Reproducibilities -- Recurrent neural networks
Аннотация: Reflection is an essential feature of consciousness and possibly the single most important one. This fact allows us to simplify the objective of the concept of 'neural correlates of consciousness' and to focus investigations on reflection itself. Reflexive games are the concentrated and pure embodiment of reflection manifestation without the addition of other higher cognitive functions. In this paper, we use the game 'matching pennies' ("Odd-Even") in order to trace the strategies and possible patterns of recurrent neural network operation. Experimental results show the splitting of all considered game patterns into two groups. A significant difference was observed in these groups of patterns, indicating a qualitative difference in game dynamics apparently due to the qualitatively different dynamic patterns of neuron excitations of the networks. A similar splitting of all players into two groups was found by other authors for human players, which differ in terms of the reflection availability. By this, we can assume that one of the causes of the splitting is that the presence of reflection in a particular group of recurrent neural networks dramatically changes the game meta-strategy. © Published under licence by IOP Publishing Ltd.

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Держатели документа:
Siberian Federal University, 2 79 Svobodny pr., Krasnoyarsk, 660041, Russian Federation
Institute of Biophysics SB RAS, Federal Research Center, Krasnoyarsk Scientific Center SB RAS, 50, Akademgorodok, Krasnoyarsk, 660036, Russian Federation

Доп.точки доступа:
Dolgova, T.; Bartsev, S.

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Recurrent and multi-layer neural networks playing Even-Odd": Reflection against regression / S. Bartsev, G. Markova // IOP Conference Series: Materials Science and Engineering : Institute of Physics Publishing, 2020. - Vol. 734: 2nd International Scientific Conference on Advanced Technologies in Aerospace, Mechanical and Automation Engineering, MIST: Aerospace 2019 (18 November 2019 through 21 November 2019, ) Conference code: 157461, Is. 1. - Ст. 012109, DOI 10.1088/1757-899X/734/1/012109
Аннотация: Reflection understood as an internal representation of the external world by the subject is the key property of consciousness. In a refined form this property is manifested in reflective games. To win a reflective game a player has to use reflection of strictly one rank higher than the opponent. So it can be assumed that there are only two game modes - when only one player uses reflection and wins and when both players use reflection but one of them chooses incorrect reflection rank. The option of random move selection is not considered since firstly, starting the game for a draw is strange, and secondly, it is technically impossible to make random moves without a special device. Experiments with recurrent neural networks playing with each other showed that the entire set of game patterns (time series of the game score) is split into two sharply different groups that can be associated with two modes mentioned above. Experiments, in which a multilayer neural network, which is basically incapable of reflection, played against a recurrent neural network, showed that a recurrent neural network has a clear advantage winning confidently in more than 90% of the games. At the same time game patterns demonstrate splitting into two sharply different groups as was observed in experiments with the game of two recurrent neural networks and in the reflexive game of living people. © Published under licence by IOP Publishing Ltd.

Scopus
Держатели документа:
Institute of Biophysics SB RAS, Federal Research Center, Krasnoyarsk Scientific Center SB RAS, 50, Akademgorodok, Krasnoyarsk, 660036, Russian Federation
Siberian Federal University, 79 Svobodny pr., Krasnoyarsk, 660041, Russian Federation

Доп.точки доступа:
Bartsev, S.; Markova, G.

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Neural networks playing 'matching pennies' with each other: reproducibility of game dynamics / T. Dolgova, S. Bartsev // INTERNATIONAL WORKSHOP ADVANCED TECHNOLOGIES IN MATERIAL SCIENCE, : IOP PUBLISHING LTD, 2019. - Vol. 537: International Workshop on Advanced Technologies in Material Science, (APR 04-06, 2019, Krasnoyarsk, RUSSIA). - Ст. 042002. - (IOP Conference Series-Materials Science and Engineering), DOI 10.1088/1757-899X/537/4/042002. - Cited References:18 . -

РУБ Engineering, Mechanical + Materials Science, Multidisciplinary
Рубрики:
REPRESENTATIONS
CONSCIOUSNESS
Аннотация: Reflection is an essential feature of consciousness and possibly the single most important one. This fact allows us to simplify the objective of the concept of 'neural correlates of consciousness' and to focus investigations on reflection itself. Reflexive games are the concentrated and pure embodiment of reflection manifestation without the addition of other higher cognitive functions. In this paper, we use the game 'matching pennies' ("Odd-Even") in order to trace the strategies and possible patterns of recurrent neural network operation. Experimental results show the splitting of all considered game patterns into two groups. A significant difference was observed in these groups of patterns, indicating a qualitative difference in game dynamics apparently due to the qualitatively different dynamic patterns of neuron excitations of the networks. A similar splitting of all players into two groups was found by other authors for human players, which differ in terms of the reflection availability. By this, we can assume that one of the causes of the splitting is that the presence of reflection in a particular group of recurrent neural networks dramatically changes the game meta-strategy.

WOS
Держатели документа:
Siberian Fed Univ, 79 Svobodny Pr, Krasnoyarsk 660041, Russia.
RAS, SB, Inst Biophys, Fed Res Ctr,Krasnoyarsk Sci Ctr, 50 Akad Gorodok, Krasnoyarsk 660036, Russia.

Доп.точки доступа:
Dolgova, T.; Bartsev, S.

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