Related papers: Identification of Interesting Objects in Large Spe…
A new continuous classification system for BL Lacertae (BL Lac) objects is proposed. The peak frequency of the synchrotron component in the $\nu L_{\nu}$ spectrum is used as a classifying parameter. The application of the accelerating inner…
Machine learning--based anomaly detection (AD) methods are promising tools for extending the coverage of searches for physics beyond the Standard Model (BSM). One class of AD methods that has received significant attention is resonant…
The emission of very-high-energy photons (VHE, E$>$100 GeV) in active galactic nuclei (AGN) is closely connected with the production of ultra-relativistic particles. Among AGN, the subclass of extreme BL Lacertae are of particular interest…
Low-resolution spectra are proved competitive to high-resolution spectra in determining many stellar labels at comparable precision. It is useful to consider the spectral information content when assessing the capability of a stellar…
Compact objects undergoing mass transfer exhibit significant (and double-peaked) $H_{\alpha}$ emission lines. Recently, new methods have been developed to identify black hole X-ray binaries (BHXBs) and calculate their systematic parameters…
The possible detection of massive quasi-stable exotic particles at the high luminosity hadronic colliders is discussed. In the coming ten years the LHC, now under preparation, has the best opportunity to observe them at the TeV scale. The…
We present the updated design of HighSpec, a high-resolution $\mathcal{R} \sim 20,000$ spectrograph designed for the Multi Aperture Spectroscopic Telescope (MAST). HighSpec offers three observing modes centered at the Ca II H&K, Mg b…
Multi-object state estimation is a fundamental problem for robotic applications where a robot must interact with other moving objects. Typically, other objects' relevant state features are not directly observable, and must instead be…
We have observed with ROSAT six blazars from the sample of 31 polarized objects constructed by Impey and Tapia (1988). Results of the spectral analysis in the ROSAT band of three objects, PKS 0301-243, PKS 1055+018 and PG 1424+240 are…
We show that the possibility to address and image single sites of an optical lattice, now an experimental reality, allows to measure the frequency-resolved local particle and hole spectra of a wide variety of one- and two-dimensional…
A machine-learning-based method is developed to identify objects with unusual stellar spectra. The method employs an autoencoder, a neural network trained to compress spectral data into a low-dimensional representation and subsequently…
We have conducted spectropolarimetry of 12 type II (obscured) quasar candidates selected from the spectroscopic database of the Sloan Digital Sky Survey based on their emission line properties. Polarization was detected in all objects, with…
Localizing targets of interest in a given hyperspectral (HS) image has applications ranging from remote sensing to surveillance. This task of target detection leverages the fact that each material/object possesses its own characteristic…
Statistical pattern recognition methods have provided competitive solutions for variable star classification at a relatively low computational cost. In order to perform supervised classification, a set of features is proposed and used to…
We present an algorithm to search for the faint spectrum of a second star mixed with the spectrum of a brighter star in high resolution spectra. We model optical stellar spectra as the sum of two input spectra drawn from a vast library of…
Boosted objects - particles whose transverse momentum is greater than twice their mass - are becoming increasingly important as the LHC continues to explore energies in the TeV range. The sensitivity of searches for new phenomena beyond the…
Chemical abundance determinations from stellar spectra are challenged by observational noise, limitations in stellar models, and departures from simplifying assumptions. While traditional and supervised machine learning methods have made…
Instance segmentation aims to delineate each individual object of interest in an image. State-of-the-art approaches achieve this goal by either partitioning semantic segmentations or refining coarse representations of detected objects. In…
Multispectral pedestrian detection has attracted increasing attention from the research community due to its crucial competence for many around-the-clock applications (e.g., video surveillance and autonomous driving), especially under…
Hyperspectral imagery provides abundant spectral information beyond the visible RGB bands, offering rich discriminative details about objects in a scene. Leveraging such data has the potential to enhance visual tracking performance. In this…