Ms. Maretta Kazaryan Profile

Maretta Kazaryan

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Publications (22)

Proceedings Article | 7 June 2024 Poster + Paper

Methodology for forecasting changes in tourist flow in conditions of emergency situations using remote sensing technologies

M. Kazaryan, M. Shakhramanian, E. Semenishchev

Proceedings Volume 13031, 130310V (2024) https://doi.org/10.1117/12.3017671

KEYWORDS: Remote sensing, Data modeling, Environmental monitoring, Mathematical modeling, Environmental sensing, Ecology, Sustainability, Satellites, Earth observing sensors, Systems modeling

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Proceedings Article | 6 June 2024 Poster

Labyrinth models for remote sensing application

M. Kazaryan, A. Rihter, E. Semenishchev

Proceedings Volume 12999, (2024) https://doi.org/10.1117/12.3024951

KEYWORDS: Raster graphics, Data processing, Binary data, Algorithm development, Transparency, Spatial resolution, Edge detection, Digital signal processing

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Proceedings Article | 15 August 2023 Poster + Paper

Robotization of engineering equipment to improve the safety of emergency rescue operations using optical methods

M. Kazaryan, M. Shakhramanyan, A. Zelensky, E. Semenishchev

Proceedings Volume 12618, 1261833 (2023) https://doi.org/10.1117/12.2678110

KEYWORDS: Robotics, Engineering, Robotic systems, Fire, Safety, Prototyping, Emergency preparedness, Control systems, Surgery, Machine vision

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Proceedings Article | 16 June 2023 Poster + Paper

Visual interpretation of building objects at the initial and final stages of the life cycle according to the satellite and ground survey data

M. Kazaryan, A. Richter, M. Shakhramanyan, E. Semenishchev

Proceedings Volume 12525, 125250N (2023) https://doi.org/10.1117/12.2666563

KEYWORDS: Satellites, Visualization, Satellite imaging, Earth observing sensors, Object detection, Engineering

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Proceedings Article | 15 June 2023 Poster + Paper

Space monitoring to control the dynamics of changes in the resource potential of the tourist business under conditions of increased risk of emergencies

M. Kazaryan, M. Shakhramanyan, E. Semenishchev

Proceedings Volume 12514, 125140L (2023) https://doi.org/10.1117/12.2666562

KEYWORDS: Remote sensing, Satellites, Vegetation, Satellite imaging, Earth observing sensors, Minerals, Ecology

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Proceedings Article | 4 January 2023 Poster + Paper

Parametric evaluation of observed objects from images based on perspective geometry methods and convolutional neural networks

M. Kazaryan, A. Richter, A. Murynin, O. Gvozdev, V. Kozub, D. Yu. Pukhovsky, A. Zelensky, E. Semenishchev

Proceedings Volume 12317, 123171E (2023) https://doi.org/10.1117/12.2646261

KEYWORDS: 3D modeling, Image segmentation, 3D image processing, Convolutional neural networks, Machine vision, Roads, Computer vision technology, Reconstruction algorithms

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Proceedings Article | 26 October 2022 Poster + Paper

Information modeling technologies in the tasks of construction and operation of buildings and structures

M. Kazaryan, M. Shakhramanyan, E. Semenishchev

Proceedings Volume 12269, 122690K (2022) https://doi.org/10.1117/12.2641135

KEYWORDS: Buildings, Data modeling, 3D modeling, Information technology, Chemical elements, Instrument modeling, Visual process modeling

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Proceedings Article | 26 October 2022 Poster + Paper

Reconstruction of 3D models of infrastructure objects from satellite images based on typed elements

M. Kazaryan, A. Richter, A. Gvozdev, A. Murynin, V. Kozub, D. Pukhovsky, M. Shakhramanyan, E. Semenishchev

Proceedings Volume 12269, 122690J (2022) https://doi.org/10.1117/12.2641134

KEYWORDS: Buildings, 3D modeling, Raster graphics, Satellites, Satellite imaging, Earth observing sensors, Image segmentation, 3D image processing, Data modeling

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Proceedings Article | 31 May 2022 Poster + Paper

The underground surface analysis of waste disposal objects based on the neural network image processing methods

M. Kazaryan, E. Semenishchev, V. Voronin

Proceedings Volume 12094, 1209410 (2022) https://doi.org/10.1117/12.2620807

KEYWORDS: Image processing, Neural networks, Image segmentation, Climate change, Satellites, Satellite imaging, Image processing algorithms and systems, Earth observing sensors, Remote sensing

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Proceedings Article | 17 May 2022 Poster + Paper

Global intelligent system for waste disposal objects monitoring using the discrete orthogonal transformations based on neural network remote sensing image processing

Maretta Kazaryan, Evgeny Semenishchev, Viacheslav Voronin

Proceedings Volume 12138, 121380V (2022) https://doi.org/10.1117/12.2625491

KEYWORDS: Fractal analysis, Image processing, Neural networks, Remote sensing, Intelligence systems, Earth observing sensors, Satellites, Satellite imaging

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Proceedings Article | 12 September 2021 Presentation + Paper

The discrete system of Fibonacci functions for the construction of a global automated system for monitoring objects littering the environment using remote sensing

M. Kazaryan, E. Semenishchev, V. Voronin

Proceedings Volume 11862, 1186206 (2021) https://doi.org/10.1117/12.2600720

KEYWORDS: Matrices, Satellites, Earth observing sensors, Satellite imaging, Multispectral imaging, Solids, Remote sensing, Image compression, Aerospace engineering

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Proceedings Article | 12 September 2021 Poster + Paper

Unauthorized landfills of solid household and industrial wastes detection in the Arctic and subarctic territories using remote sensing technologies

M. Kazaryan, M. Shahramanian, E. Semenishchev

Proceedings Volume 11856, 1185619 (2021) https://doi.org/10.1117/12.2600721

KEYWORDS: Solids, Snow cover, Remote sensing, Raster graphics, Vegetation, Pollution, Earth observing sensors, Temperature metrology, Landsat, Water

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Proceedings Article | 3 August 2021 Poster + Paper

Research of the impact of solid domestic and industrial waste on the snow and ice coverage of mountain territories of the Northern Caucasus using remote sensing technology

M. Kazaryan, E. Semenishchev, V. Voronin

Proceedings Volume 11829, 118291C (2021) https://doi.org/10.1117/12.2598314

KEYWORDS: Solids, Snow cover, Remote sensing, Raster graphics, Earth observing sensors, Vegetation, Temperature metrology, Tongue, Satellites, Landsat

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Proceedings Article | 12 April 2021 Poster + Paper

Satellite image processing based on percolation for physicochemical analysis of soil cover of industrial waste facilities

M. Kazaryan, V. Voronin

Proceedings Volume 11755, 117550W (2021) https://doi.org/10.1117/12.2587769

KEYWORDS: Soil science, Satellites, Satellite imaging, Earth observing sensors, Image processing, Remote sensing, Chemical analysis, Wigner distribution functions, Solids, Spatial resolution

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Proceedings Article | 20 September 2020 Poster + Paper

Analysis of the underlying surface of waste disposal facilities using remote sensing technologies

M. Kazaryan, M. A. Shakhramanyan, V. Voronin

Proceedings Volume 11533, 115331K (2020) https://doi.org/10.1117/12.2574135

KEYWORDS: Remote sensing, Solids, Satellite imaging, Earth observing sensors, Satellites, Space operations, Image analysis, Image filtering, Computer simulations, Stochastic processes

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Proceedings Article | 18 May 2020 Paper

Research of percolation at objects for waste disposal according to space image data

M. Kazaryan, V. Voronin

Proceedings Volume 11397, 113970K (2020) https://doi.org/10.1117/12.2558427

KEYWORDS: Solids, Image analysis, Process modeling, Chemical analysis, Remote sensing, Mathematical modeling

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Proceedings Article | 2 October 2019 Paper

Construction of 3D models of the Earth's surface in urban environments using remote sensing technologies

A. Richter, M. Kazaryan, M. Shahramanian, V. Voronin

Proceedings Volume 11157, 111570W (2019) https://doi.org/10.1117/12.2534749

KEYWORDS: Remote sensing, Environmental sensing, Process modeling, 3D modeling, Spatial resolution, Computer programming, Buildings, Roads, MATLAB

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Proceedings Article | 27 June 2019 Paper

Fractal presentation of space images during waste disposal sites monitoring

Maretta Kazaryan, Mikhail Shakhramanyan, Roumen Nedkov, Denitsa Borisova, Daniela Avetisyan

Proceedings Volume 11174, 111741O (2019) https://doi.org/10.1117/12.2532890

KEYWORDS: Fractal analysis, Image processing, Mathematical modeling, Aerospace engineering, Signal processing, Signal detection, Data modeling, Scattering, Satellite imaging, Satellites

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While constructing a mathematical model of the space observation system for information processing of the data of monitoring the territories on the presence of the waste disposal sites (WDS), we have a stochastic process with a fractal structure. The physical processes of the WDS are formed under the influence of thermal, chemical, etc. factors. There are different methods and approaches for describing the scattering and radiating surfaces of the objects that make up solid household and industrial waste using single-scale and multi-scale correlation radii. With an increase in the order of multi-scale, the multi-scale of the correlation radius also increases, and this, accordingly, complicates the construction of a mathematical model of a space image. The transition to the fractal presentation of the image allows solving the problem of the space images processing. The paper proposes some algorithm for processing the aerospace images using a field of fractal dimension. The theoretical and experimental studies are being held with respect to improving the results of aerospace image classification results while monitoring for the WDS presence. An assessment of the size of the “window” and the magnitude of the “jump” on the parameters of the fractal dimensions is also made. The purpose of the work is to describe the system synergistic approach of multi-scale selection, which allows overcoming the problems of the image processing. This is due to incomplete knowledge of signals, non-stationarity, non- Markov, noise singularity based on preliminary information about the spatial scales of the detected signals. While working with low-contrast images, the usual signal processing technique (contour-texture, spectral methods) does not adequate. There is a need to apply the theory of fractals in the study of processes occurring on the surface of the WDS through remote sensing. An experiment is carried out using the example of fractals, an image is decoded. The features of fractals are considered.

Proceedings Article | 9 October 2018 Paper

The automated space-monitoring system of waste disposal sites

M. Kazaryan, M. Shahramanian, V. Voronin

Proceedings Volume 10793, 1079318 (2018) https://doi.org/10.1117/12.2500059

KEYWORDS: Image processing, Databases, Satellites, Solids, Satellite imaging, Earth observing sensors, Wavelet transforms, Mathematical modeling, Wavelets, Environmental monitoring

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Proceedings Article | 10 October 2017 Paper

Research of generalized wavelet transformations of Haar correctness in remote sensing of the Earth

Maretta Kazaryan, Mihail Shakhramanyan, Roumen Nedkov, Andrey Richter, Denitsa Borisova, Nataliya Stankova, Iva Ivanova, Mariana Zaharinova

Proceedings Volume 10427, 104271U (2017) https://doi.org/10.1117/12.2278572

KEYWORDS: Wavelets, Remote sensing, Satellite imaging, Earth observing sensors, Satellites, Image processing, Space operations, Transform theory, Wavelet transforms, Image filtering

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In this paper, Haar's generalized wavelet functions are applied to the problem of ecological monitoring by the method of remote sensing of the Earth. We study generalized Haar wavelet series and suggest the use of Tikhonov's regularization method for investigating them for correctness. In the solution of this problem, an important role is played by classes of functions that were introduced and described in detail by I.M. Sobol for studying multidimensional quadrature formulas and it contains functions with rapidly convergent series of wavelet Haar. A theorem on the stability and uniform convergence of the regularized summation function of the generalized wavelet-Haar series of a function from this class with approximate coefficients is proved. The article also examines the problem of using orthogonal transformations in Earth remote sensing technologies for environmental monitoring. Remote sensing of the Earth allows to receive from spacecrafts information of medium, high spatial resolution and to conduct hyperspectral measurements. Spacecrafts have tens or hundreds of spectral channels. To process the images, the device of discrete orthogonal transforms, and namely, wavelet transforms, was used. The aim of the work is to apply the regularization method in one of the problems associated with remote sensing of the Earth and subsequently to process the satellite images through discrete orthogonal transformations, in particular, generalized Haar wavelet transforms. General methods of research. In this paper, Tikhonov's regularization method, the elements of mathematical analysis, the theory of discrete orthogonal transformations, and methods for decoding of satellite images are used. Scientific novelty. The task of processing of archival satellite snapshots (images), in particular, signal filtering, was investigated from the point of view of an incorrectly posed problem. The regularization parameters for discrete orthogonal transformations were determined.

Proceedings Article | 6 September 2017 Paper

Quality enhancement of satellite images and its application for identification of surroundings of waste disposal sites

Andrey Richter, Maretta Kazaryan, Mihail Shakhramanyan, Roumen Nedkov, Denitsa Borisova, Nataliya Stankova, Iva Ivanova, Mariana Zaharinova

Proceedings Volume 10444, 104441N (2017) https://doi.org/10.1117/12.2277309

KEYWORDS: Satellite imaging, Earth observing sensors, Satellites, Pattern recognition, Image quality

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Proceedings Article | 23 May 2017 Presentation + Paper

Pattern recognition algorithm using descriptors combined radio and visible spectra

A. Richter, M. Kazaryan, M. Shakhramanyan, V. Voronin

Proceedings Volume 10221, 1022107 (2017) https://doi.org/10.1117/12.2262875

KEYWORDS: Infrared radiation, Pattern recognition, Multimedia, Earth observing sensors, Radar, Solids, Satellite imaging, Satellites, Image filtering, Image processing, Buildings, Detection and tracking algorithms, Remote sensing

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Showing 5 of 22 publications

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