Related papers: A Classifier to Detect Elusive Astronomical Object…
By comparing near-infrared spectra with atmosphere models, we infer the effective temperature, surface gravity, projected rotational velocity, and radial velocity for 21 very-low-mass stars and brown dwarfs. The unique sample consists of…
The census of the solar neighborhood is almost complete for stars and becoming more complete in the brown dwarf regime. Spectroscopic, photometric and kinematic characterization of nearby objects helps us to understand the local mass…
Thirty years after the discovery of brown dwarfs, the search for these objects continues, particularly in the vicinity of the Sun. Objects near the Sun are characterized by large proper motions, making them seen as fast-moving objects.…
In the field of object classification, identification based on object variations is a challenge in itself. Variations include shape, size, color, and texture, these can cause problems in recognizing and distinguishing objects accurately.…
We present low-resolution (R=900) optical (576.1--1,051.1 nm) spectroscopic observations of 40 candidate very low-mass members in the Upper Scorpius OB association. These objects were selected using the $I$, $J$ and $K$ photometry available…
New generation large-aperture telescopes, multi-object spectrographs, and large format detectors are making it possible to acquire very large samples of stellar spectra rapidly. In this context, traditional star-by-star spectroscopic…
We present near-infrared (1.15-2.50 microns) medium-resolution (R = 1700) spectroscopy of a sample of 23 brown dwarf candidates in the young Upper Sco association. We confirm membership of 21 brown dwarfs based on their spectral shape,…
The estimation of the optical properties of a material from RGB-images is an important but extremely ill-posed problem in Computer Graphics. While recent works have successfully approached this problem even from just a single photograph,…
Context. In modern astronomy, machine learning has proved to be efficient and effective to mine the big data from the newesttelescopes. Spectral surveys enable us to characterize millions of objects, while long exposure time observations…
We provide classifications for all 143 million non-repeat photometric objects in the Third Data Release of the Sloan Digital Sky Survey (SDSS) using decision trees trained on 477,068 objects with SDSS spectroscopic data. We demonstrate that…
We describe a new method of combining optical and infrared photometry to select Luminous Red Galaxies (LRGs) at redshifts $z > 0.6$. We explore this technique using a combination of optical photometry from CFHTLS and HST, infrared…
Our aim is to compile a catalog of white dwarfs within 40 parsecs of the Sun, in which newly discovered objects would significantly increase the completeness of the current census. White dwarf candidates are identified from the SUPERBLINK…
Machine learning, and eventually true artificial intelligence techniques, are extremely important advancements in astrophysics and astronomy. We explore the application of deep learning using neural networks in order to automate the…
In the third catalog of active galactic nuclei detected by the Fermi-LAT (3LAC) Clean Sample, there are 402 blazars candidates of uncertain type (BCU). Due to the limitations of astronomical observation or intrinsic properties, it is…
The next generation of observatories will facilitate the discovery of new types of astrophysical transients. The detection of such phenomena, whose characteristics are presently poorly constrained, will hinge on the ability to perform blind…
Magnetic Bright Points (MBPs) in the internetwork are among the smallest objects in the solar photosphere and appear bright against the ambient environment. An algorithm is presented that can be used for the automated detection of the MBPs…
We describe the development of a system for an automated, iterative, real-time classification of transient events discovered in synoptic sky surveys. The system under development incorporates a number of Machine Learning techniques, mostly…
We apply classical machine vision and machine deep learning methods to prototype signal classifiers for the search for extraterrestrial intelligence. Our novel approach uses two-dimensional spectrograms of measured and simulated radio…
We present a new method for differentiating between planetary transits and eclipsing binaries based on the presence of the ellipsoidal light variations. These variations can be used to detect stellar secondaries with masses ~0.2 M_sun…
Flares are a well-studied aspect of the Sun's magnetic activity. Detecting and classifying solar flares can inform the analysis of contamination caused by stellar flares in exoplanet transmission spectra. In this paper, we present a…