Results 21 to 30 of about 2,528,028 (339)
SDSS-DR12 Bulk Stellar Spectral Classification: Artificial Neural Networks Approach [PDF]
Astrophysics and Space Science, 2016 This paper explores the application of Probabilistic Neural Network (PNN), Support Vector Machine (SVM) and Kmeans clustering as tools for automated classification of massive stellar spectra.
S. Kheirdastan, Mahdi Bazarghan
arxiv +3 more sources
KEPLERINPUT CATALOG: PHOTOMETRIC CALIBRATION AND STELLAR CLASSIFICATION [PDF]
The Astronomical Journal, 2011 We describe the photometric calibration and stellar classification methods used to produce the Kepler Input Catalog (KIC). The KIC is a catalog containing photometric and physical data for sources in the Kepler Mission field of view; it is used by the mission to select optimal targets.
Everett, Mark +3 more
openaire +6 more sources
NutMaat: A Python package for stellar spectral classification on the MK system [PDF]
arXivStellar spectral classification according to the Morgan-Keenan (MK) system remains fundamental to astrophysical studies, yet modern surveys require automated, scalable tools. We present NutMaat, a Python-based package inspired by MKCLASS, designed to automate MK classification while addressing scalability and usability limitations.
R. El-Kholy, Z. M. Hayman
arxiv +3 more sources
Classification of large-scale stellar spectra based on the non-linearly assembling learning machine [PDF]
, 2015 An important problem to be solved of traditional classification methods is they cannot deal with large-scale classification because of very high time complexity. In order to solve above problem, inspired by the thinking of collaborative management, the non-
Zhongbao Liu, Lipeng Song, Wenjuan Zhao
openalex +2 more sources
Automated stellar classification for large surveys: a review of methods and results [PDF]
arXiv, 2001 Current and future large astronomical surveys will yield multiparameter databases on millions or even billions of objects. The scientific exploitation of these will require powerful, robust, and automated classification tools tailored to the specific survey.
C. A. L. Bailer-Jones
arxiv +3 more sources
Machine Learning Techniques for Stellar Light Curve Classification [PDF]
The Astronomical Journal, 2018 AbstractWe apply machine learning techniques in an attempt to predict and classify stellar properties from noisy and sparse time-series data. We preprocessed over 94 GB ofKeplerlight curves from the Mikulski Archive for Space Telescopes (MAST) to classify according to 10 distinct physical properties using both representation learning and feature ...
Kevin Tat +4 more
openaire +7 more sources
Stellar classification from single-band imaging using machine learning [PDF]
, 2016 Information on the spectral types of stars is of great interest in view of the exploitation of space-based imaging surveys. In this article, we investigate the classification of stars into spectral types using only the shape of their diffraction pattern ...
T. Kuntzer, M. Tewes, F. Courbin
openalex +3 more sources
Commission 29. (Stellar Classification.) [PDF]
Transactions of the International Astronomical Union, 1933 The Commission held two meetings and the time was taken up almost entirely in a discussion of stellar classification.Dr J. S. Plaskett moved, seconded by Miss Payne, that a sub-committee be appointed to consider the classification of Wolf Rayet and related spectra.The committee was appointed as follows: Miss C. H. Payne, Prof. H. H. Plaskett, Dr C.
H. N. Russell, C. S. Beals
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A machine-vision method for automatic classification of stellar halo substructure [PDF]
Monthly notices of the Royal Astronomical Society, 2019 Tidal debris structures formed from disrupted satellites contain important clues about the assembly histories of galaxies. To date, studies of these structures have been hampered by reliance on by-eye identification and morphological classification ...
David Hendel +3 more
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Application of self-organizing map to stellar spectral classifications [PDF]
Astrophysics and Space Science, 2011 We present an automatic, fast, accurate and robust method of classifying astronomical objects. The Self Organizing Map (SOM) as an unsupervised Artificial Neural Network (ANN) algorithm is used for classification of stellar spectra of stars. The SOM is used to make clusters of different spectral classes of Jacoby, Hunter and Christian (JHC) library ...
openaire +4 more sources