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Your search keyword '"Astsatryan, H."' showing total 3 results
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3 results on '"Astsatryan, H."'

1. Ten Years of the Armenian Virtual Observatory.

Author

Mickaelian, Areg M., Astsatryan, H. V., Knyazyan, A. V., Magakian, T. Yu., Mikayelyan, G. A., Erastova, L. K., Hovhannisyan, L. R., Sargsyan, L. A., and Sinamyan, P. K.

Published
2016

2. Astronomical objects classification based on the Digitized First Byurakan Survey low-dispersion spectra.

Author

Astsatryan, H., Gevorgyan, G., Knyazyan, A., Mickaelian, A., and Mikayelyan, G.A.

Subjects
CONVOLUTIONAL neural networks, DEEP learning, MACHINE learning, GALAXY spectra, CLASSIFICATION, PRISMS
Abstract

The Digitized First Byurakan Survey is the largest and the first systematic objective-prism survey of the extragalactic sky. The detection, extraction, and classification of about 40 million spectra of about 20 million astronomical objects available in the survey require distinguishing the pixels containing photons from the source and the noise pixels per object. This paper aims at developing a service to classify the spectra of UV-excess galaxies, quasars, compact galaxies, and other objects in the survey. Supervised and unsupervised convolutional neural network deep learning algorithms have been developed and studied. [ABSTRACT FROM AUTHOR]

Published
2021
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3. Astronomical objects classification based on the Digitized First Byurakan Survey low-dispersion spectra

Author

Astsatryan, H., Gevorgyan, G., Knyazyan, A., Mickaelian, A., and Mikayelyan, G.A.

Abstract

The Digitized First Byurakan Survey is the largest and the first systematic objective-prism survey of the extragalactic sky. The detection, extraction, and classification of about 40 million spectra of about 20 million astronomical objects available in the survey require distinguishing the pixels containing photons from the source and the noise pixels per object. This paper aims at developing a service to classify the spectra of UV-excess galaxies, quasars, compact galaxies, and other objects in the survey. Supervised and unsupervised convolutional neural network deep learning algorithms have been developed and studied.

Published
2021
Full Text
View/download PDF

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