Astronomy and Astrophysics

Machine learning technique for morphological classification of galaxies from the SDSS. III. CNN image-based inference of detailed features

1Khramtsov V, 2Vavilova IB, 2Dobrycheva DV, 2Vasylenko MYu., 2Melnyk OV, 2Elyiv AA, 3Akhmetov VS, 1Dmytrenko AM. Machine learning technique for morphological classification of galaxies from the SDSS. III. CNN image-based inference of detailed features. Space Science and Technology. 2022 ;28(5):03-03.

Star occultation by small bodies of the Solar system: current state of observations in Ukraine

1Kleshchonok VV, 2Karbovsky VI, 1Buromsky MI, 2Lashko MV, 3Gorbanev Yu.M, 3Kashuba VI, 3Kimakovskiy SR, 2Shavlovskiy VI, 4Angelskiy OV, 5Tsekhmeistrenko VS, et al. Star occultation by small bodies of the Solar system: current state of observations in Ukraine. Space Science and Technology. 2022 ;28(5):06-06.

Creation of the Ukrainian meteor observation network: instruments, methods for processing, observatin possibilities

1Golubaev AV, 2Gorbanev Yu.M, 3Shulga OV, 4Andreev ОА, 3Bushuev FI, 5Vidmachenko AP, 6Hrudynin BO, 5Zhilyaev BE, 3Kaliuzhnyi MP, 7Kozak PM, et al. Creation of the Ukrainian meteor observation network: instruments, methods for processing, observatin possibilities. Space Science and Technology. 2022 ;28(4):39-70.

Machine learning technique for morphological classification of galaxies from SDSS. II. The image-based morphological catalogs of galaxies at 0.02<z<0.1

1Vavilova IB, 2Khramtsov V, 1Dobrycheva DV, 1Vasylenko MYu., 1Elyiv AA, 1Melnyk OV. Machine learning technique for morphological classification of galaxies from SDSS. II. The image-based morphological catalogs of galaxies at 0.02. Space Science and Technology. 2022 ;28(1):03-22.

Astronomical observations and monitoring surveys of the Earth from the surface or from the Moon’s orbit and their ground support

1Vidmachenko AP, 2Kazantseva LV, 1Morozhenko OV, 3Choliy VYa., 1Nevodovsky PV. Astronomical observations and monitoring surveys of the Earth from the surface or from the Moon’s orbit and their ground support. Space Science and Technology. 2019 ;25(5):25-75.

On the possibility of detection of charged massive particles of dark matter from the board of artificial satellites by acoustic method

1Golubnichii PI, 1Kudlenko VO, 1Reshetnyak DV. On the possibility of detection of charged massive particles of dark matter from the board of artificial satellites by acoustic method. Kosm. nauka tehnol. 2003 ;9(Supplement1):068-071.

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