Related papers: How to measure metallicity from five-band photomet…

We present a robust method to estimate the redshift of galaxies using Pan-STARRS1 photometric data. Our method is an adaptation of the one proposed by Beck et al. (2016) for the SDSS Data Release 12. It uses a training set of 2313724…

We explore the application of computer vision and machine learning (ML) techniques to predict material properties (e.g. compressive strength) based on SEM images. We show that it's possible to train ML models to predict materials…

We infer stellar metallicity and abundance ratio gradients for a sample of red galaxies in the Sloan Digital Sky Survey (SDSS) Main galaxy sample. Because this sample does not have multiple spectra at various radii in a single galaxy, we…

We present a neural network based approach to the determination of photometric redshift. The method was tested on the Sloan Digital Sky Survey Early Data Release (SDSS-EDR) reaching an accuracy comparable and, in some cases, better than SED…

Large-scale surveys make huge amounts of photometric data available. Because of the sheer amount of objects, spectral data cannot be obtained for all of them. Therefore it is important to devise techniques for reliably estimating physical…

Obtaining gold standard annotated data for object detection is often costly, involving human-level effort. Semi-supervised object detection algorithms solve the problem with a small amount of gold-standard labels and a large unlabelled…

We present recent results from the Laboratory for Cosmological Data Mining (http://lcdm.astro.uiuc.edu) at the National Center for Supercomputing Applications (NCSA) to provide robust classifications and photometric redshifts for objects in…

The impressive growth of data throughput in optical microscopy has triggered a widespread use of supervised learning (SL) models running on compressed image datasets for efficient automated analysis. However, since lossy image compression…

Stellar metallicity strongly correlates with the presence of planets and their properties. To check for new correlations between stars and the existence of an orbiting planet, we determine precise stellar parameters for a sample of…

The percolation threshold is an important measure to determine the inherent rigidity of large networks. Predictors of the percolation threshold for large networks are computationally intense to run, hence it is a necessity to develop…

Context. Several new techniques to determine the metallicity of M dwarfs with better precision have been developed over the last decades. However, most of these studies were based on empirical methods. In order to enable detailed abundance…

Machine learning techniques are utilized to estimate the electronic band gap energy and forecast the band gap category of materials based on experimentally quantifiable properties. The determination of band gap energy is critical for…

Depth estimation from 2D images is a common computer vision task that has applications in many fields including autonomous vehicles, scene understanding and robotics. The accuracy of a supervised depth estimation method mainly relies on the…

With the aim of using machine learning techniques to obtain photometric redshifts based upon a source's radio spectrum alone, we have extracted the radio sources from the Million Quasars Catalogue. Of these, 44,119 have a spectroscopic…

Determining photometric redshifts to high accuracy is paramount to measure distances in wide-field cosmological experiments. With only photometric information at hand, photo-zs are prone to systematic uncertainties in the intervening…

Deriving metallicities for solar-like stars follows well-established methods, but for cooler stars such as M dwarfs, the determination is much more complicated due to forests of molecular lines that are present. Several methods have been…

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…

Radio Frequency Identification (RFID) tracking may be a viable solution for defense assets that must be stored in accordance with security guidelines. However, poor sensor specificity (vulnerabilities include long range detection, spoofing,…

Knowledge of stellar atmospheric parameters ($T_{\rm eff}$, $\log{g}$, [Fe/H]) of M dwarfs can be used to constrain both theoretical stellar models and Galactic chemical evolutionary models, and guide exoplanet searches, but their…

We used 5487 star-forming galaxies at redshift z~0.63 extracted from the VIPERS and 143774 comparison galaxies in the local Universe from the GSWLC catalog. We employed two families of methods: parametric and non-parametric. In the former…