Related papers: Classifying white dwarfs from multi-object spectro…
It is observed that high classification performance is achieved for one- and two-dimensional signals by using deep learning methods. In this context, most researchers have tried to classify hyperspectral images by using deep learning…
The space density of white dwarfs is highly uncertain even nearby. This results from the fact that the known sample of white dwarfs is largely incomplete in part because most white dwarfs have been discovered as by-products in non-dedicated…
Laser absorption spectroscopy (LAS) is a well-established technique for non-intrusive measurement of gas species in combustion and atmospheric environments, but conventional methods struggle with multi-species mixtures under dynamic or…
Context. White dwarf-main sequence (WDMS) binaries are used to study several different important open problems in modern astrophysics. Aims. The Sloan Digital Sky Survey (SDSS) identified the largest catalogue of WDMS binaries currently…
Stellar spectral classification is a fundamental tool of modern astronomy, providing insight into physical characteristics such as effective temperature, surface gravity, and metallicity. Accurate and fast spectral typing is an integral…
This paper investigates tree species classification using Sentinel-2 multispectral satellite image time-series. Despite their critical importance for many applications, such maps are often unavailable, outdated, or inaccurate for large…
We present spectra for 33 previously unclassified white dwarf systems brighter than V = 17 primarily in the southern hemisphere. Of these new systems, 26 are DA, 4 are DC, 2 are DZ, and 1 is DQ. We suspect three of these systems are…
Raman spectroscopy is an important characterization tool with diverse applications in many areas of research. We propose a machine learning method for predicting polarizabilities with the goal of providing Raman spectra from molecular…
This paper proposes a novel automatic classification framework for the recognition of five types of white blood cells. Segmenting complete white blood cells from blood smears images and extracting advantageous features from them remain…
We use hierarchical Bayesian modelling to calibrate a network of 32 all-sky faint DA white dwarf (DA WD) spectrophotometric standards ($16.5 < V < 19.5$) alongside three CALSPEC standards, from 912 \r{A} to 32 $\mu$m. The framework is the…
Symmetry is a key feature observed in nature (from flowers and leaves, to butterflies and birds) and in human-made objects (from paintings and sculptures, to manufactured objects and architectural design). Rotational, translational, and…
Pattern recognition and image classification are essential tasks in machine vision. Autonomous vehicles, for example, require being able to collect the complex information contained in a changing environment and classify it in real time.…
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…
Discrete return (DR) Laser Detection and Ranging (Ladar) systems provide a series of echoes that reflect from objects in a scene. These can be first, last or multi-echo returns. In contrast, Full-Waveform (FW)-Ladar systems measure the…
We demonstrate the use of deep learning for fast spectral deconstruction of speckle patterns. The artificial neural network can be effectively trained using numerically constructed multispectral datasets taken from a measured spectral…
We report an independent spectral classification of a sample of poorly studied M-dwarf candidate stars observed with the OSIRIS instrument at GTC. Our project was carried out as an independent test of the spectral classification. It is…
We present a novel approach for classifying stars as binary or exoplanet using deep learning techniques. Our method utilizes feature extraction, wavelet transformation, and a neural network on the light curves of stars to achieve…
Laser cutting is a widely adopted technology in material processing across various industries, but it generates a significant amount of dust, smoke, and aerosols during operation, posing a risk to both the environment and workers' health.…
We present first results from a major program of methane filter photometry for low-mass stars and brown dwarfs. The definition of a new methane filter photometric system is described. A recipe is provided for the differential calibration of…
We investigate applications of machine learning models to directly infer physical properties of brown dwarfs from their photometry and spectra using $\textit{The Cannon}$. We demonstrate that absolute magnitudes, spectral types, and…