Related papers: Variable star classification with a Multiple-Input…

Discoveries of RR Lyrae and Cepheid variable stars with multiple modes of pulsation have increased tremendously in recent years. The Fourier spectra of these stars can be quite complicated due to the large number of combination frequencies…

In this paper we present the WeCAPP variable star catalogue towards the bulge of M31. The observations of the WeCAPP microlensing survey (optical R and I bands) during three years (2000-2003) result in a database with unprecedented time…

Increasing deployment of photovoltaic (PV) plants requires methods for automatic detection of faulty PV modules in modalities, such as infrared (IR) images. Recently, deep learning has become popular for this. However, related works…

Next-generation radio surveys will yield an unprecedented amount of data, warranting analysis by use of machine learning techniques. Convolutional neural networks are the deep learning technique that has proven to be the most successful in…

The classification of different grapevine varieties is a relevant phenotyping task in Precision Viticulture since it enables estimating the growth of vineyard rows dedicated to different varieties, among other applications concerning the…

Deep neural networks can be effective means to automatically classify aerial images but is easy to overfit to the training data. It is critical for trained neural networks to be robust to variations that exist between training and test…

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. To process this information and to extract all possible knowledge, machine learning…

We have started a survey of M 33 in order to find variable stars and Cepheids in particular. We have obtained more than 30 epochs of g'r'i' data with the CFHT and the one-square-degree camera MegaCam. We present first results from this…

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…

Binary stars are prevalent yet challenging to detect. We present a novel approach using convolutional neural networks (CNNs) to identify binary stars from low-resolution spectra obtained by the LAMOST survey. The CNN is trained on a dataset…

The EXTraS project, based on data collected with the XMM-Newton observatory, provided us with a vast amount of light curves for X-ray sources. For each light curve, EXTraS also provided us with a set of features (https://extras.inaf.it). We…

We present a variability study of 4646 massive stars in the Small Magellanic Cloud (SMC) with known spectral types from the catalog of Bonanos et al. (2010) using the light curves from the OGLE-III database. The goal is to exploit the time…

This work presents and analyzes three convolutional neural network (CNN) models for efficient pixelwise classification of images. When using convolutional neural networks to classify single pixels in patches of a whole image, a lot of…

The distinction between stars and galaxies is a fundamental problem in the field of celestial classification. This issue has become challenging for these ongoing and upcoming digital surveys, which will produce terabytes and even petabytes…

M71 is a nearby, metal-rich globular cluster at low Galactic latitude, where field contamination and spatially variable extinction complicate colour-magnitude diagrams (CMDs) and the identification of cluster member variable stars. Our aims…

Classical Cepheids are not only excellent standard candles, but also invaluable tools to test stellar evolution and pulsation theories. Rates of their pulsation period change, quantified usually through $O-C$ diagrams, can be confronted…

The plethora of spectra of OB-type stars in observatory archives and the much larger numbers to come from the WEAVE and 4MOST spectroscopic facilities require efficient, but also accurate and precise methods for (semi)automatic quantitative…

We analyse photometry for 138 first overtone Cepheids from the Small Magellanic Cloud, in which Optical Gravitational Lensing Experiment (OGLE) team discovered additional variability with period shorter than first overtone period, and…

We present a nearly complete collection of type II Cepheids in the Magellanic System. The sample consists of 338 objects: 285 and 53 variables in the Large and Small Magellanic Clouds, respectively. Based on the pulsation periods and…

Periodic variables illuminate the physical processes of stars throughout their lifetime. Wide-field surveys continue to increase our discovery rates of periodic variable stars. Automated approaches are essential to identify interesting…