Related papers: Classifying white dwarfs from multi-object spectro…
Aims. The derivation of spectroscopic parameters for M dwarf stars is very important in the fields of stellar and exoplanet characterization. The goal of this work is the creation of an automatic computational tool, able to derive quickly…
Innovation in the ground and space-based instruments has taken us into a new age of spectroscopy, in which a large amount of stellar content is becoming available. So, automatic classification of stellar spectra became subjective in recent…
We aim at building a method that efficiently identifies young low-mass stars and brown dwarfs from low-resolution near-infrared spectra, by studying gravity-sensitive features and their evolution with age. We built a dataset composed of all…
Detecting and classifying targets in video streams from surveillance cameras is a cumbersome, error-prone and expensive task. Often, the incurred costs are prohibitive for real-time monitoring. This leads to data being stored locally or…
In powder diffraction data analysis, phase identification is the process of determining the crystalline phases in a sample using its characteristic Bragg peaks. For multiphasic spectra, we must also determine the relative weight fraction of…
We describe automatic procedures for the selection of DA white dwarfs in the Hamburg/ESO objective-prism survey (HES). For this purpose, and the selection of other stellar objects (e.g., metal-poor stars and carbon stars), a flexible,…
By selecting astrometric and photometric data from the Sloan Digital Sky Survey (SDSS), the L{\'e}pine & Shara Proper Motion North Catalog (LSPM-North), the Two Micron All Sky Survey (2MASS), and the USNO-B1.0 catalog, we use a succession…
Automatic modulation classification is of crucial importance in wireless communication networks. Deep learning based automatic modulation classification schemes have attracted extensive attention due to the superior accuracy. However, the…
We show that Milky Way white dwarfs are excellent targets for dark matter (DM) detection. Using Fermi and H.E.S.S. Galactic center gamma-ray data, we investigate sensitivity to DM annihilating within white dwarfs into long-lived or boosted…
Recent studies of the stellar population in the solar neighborhood (<20 pc) suggest that there are undetected white dwarfs (WDs) in multiple systems with main sequence companions. Detecting these hidden stars and obtaining a more complete…
This paper presents a deep learning approach to the classification of 160 shortwave radio signals. It addresses the typical challenges of the shortwave spectrum, which are the large number of different signal types, the presence of various…
We present a catalogue of 1602 white dwarf-main sequence binaries (WDMS) from the spectroscopic Sloan Digital Sky Survey Data Release 6 (SDSS DR6). Among these we identify 440 as new WDMS binaries. We select WDMS binary candidates from…
Magnetic white dwarfs with field strengths below 10 MG are easy to recognise since the Zeeman splitting of spectral lines appears proportional to the magnetic field strength. For fields $\geq 100$ MG, however, transition wavelengths become…
The purpose of this study was to investigate the use of deep learning for coniferous/deciduous classification of individual trees from airborne LiDAR data. To enable efficient processing by a deep convolutional neural network (CNN), we…
We present an image classification algorithm using deep learning convolutional neural network architecture, which classifies the morphologies of eclipsing binary systems based on their light curves. The algorithm trains the machine with…
Prior work on plant species classification predominantly focuses on building models from isolated plant attributes. Hence, there is a need for tools that can assist in species identification in the natural world. We present a novel and…
Over the past several decades, conventional spectral analysis techniques of polluted white dwarfs have become powerful tools to learn about the geology and chemistry of extrasolar bodies. Despite their proven capabilities and extensive…
We present an homogeneous analysis of all DA stars labeled as magnetic in the Montreal White Dwarf Database (MWDD). Our sample is restricted to almost all known magnetic white dwarf showing clear sign of splitting ($B \gtrsim$ 1-2 MG) that…
White dwarfs in globular clusters offer additional possibilities to determine distances and ages of globular clusters, provided their spectral types and masses are known. We therefore started a project to obtain spectra of white dwarfs in…
The spectroscopic catalogue of white dwarf-main sequence (WDMS) binaries from the Sloan Digital Sky Survey (SDSS) is the largest and most homogeneous sample of compact binary stars currently known. However, because of selection effects, the…