Related papers: A neural network-based methodology to select young…
Research on young stellar populations is essential to understand the properties of embedded clusters and advance theories of their formation. This has driven advancements in methodologies for star detection, leading to the development of…
Modern X-ray telescopes have detected hundreds of thousands of X-ray sources in the universe. However, current methods to classify these sources using the X-ray data themselves suffer problems - detailed X-ray spectroscopy of individual…
With the Wide-Field Infrared Survey Explorer (WISE), we searched for young stellar objects (YSOs) in a 100 deg^2 region centered on the lightly studied Canis Major star forming region. Applying stringent magnitude cuts to exclude the…
Artificial neural networks (ANN) have been successfully used in the last years to identify patterns in astronomical images. The use of ANN in the field of asteroid dynamics has been, however, so far somewhat limited. In this work we used…
Classifying and summarizing large data sets from different sky survey projects is essential for various subsequent scientific research. By combining data from 4XMM-DR13, SDSS DR18, and CatWISE, we formed an XMM-WISE-SDSS sample that…
We demonstrate the use of the AKARI survey photometric data in the study of galactic star formation. Our aim was to select young stellar objects (YSOs) in the AKARI FIS catalogue. We used AKARI Far-Infrared Surveyor and Wide-field Infrared…
The HII complex N44 in the Large Magellanic Cloud (LMC) provides an excellent site to perform a detailed study of star formation in a mild starburst, as it hosts three regions of star formation at different evolutionary stages and it is not…
We present a survey of the Orion A and B molecular clouds undertaken with the IRAC and MIPS instruments onboard Spitzer. In total, five distinct fields were mapped covering 9 sq. degrees in five mid-IR bands spanning 3-24 microns. The…
We explored the AllWISE catalogue of the Wide-field Infrared Survey Explorer mission and identified Young Stellar Object candidates. Reliable 2MASS and WISE photometric data combined with Planck dust opacity values were used to build our…
We present an analysis of Young Stellar Object (YSO) candidates towards the LDN 1188 molecular cloud. The YSO candidates were selected from the WISE all-sky catalogue, based on a statistical method. We found 601 candidates in the region,…
Single particle imaging (SPI) is a promising method for native structure determination which has undergone a fast progress with the development of X-ray Free-Electron Lasers. Large amounts of data are collected during SPI experiments,…
With nearly two billion stars observed and their corresponding astrometric parameters evaluated in the recent Gaia mission, the number of astrometric binary candidates have risen significantly. Due to the surplus of astrometric data, the…
Spiking Neural Networks (SNNs) have garnered widespread interest for their energy efficiency and brain-inspired event-driven properties. While recent methods like Spiking-YOLO have expanded the SNNs to more challenging object detection…
We present a spectroscopic follow-up of photometrically-selected young stellar object (YSO) candidates in the Central Molecular Zone of the Galactic center. Our goal is to quantify the contamination of this YSO sample by reddened giant…
We investigate the distribution of different classes of spectroscopically identified sources and theoretical models in the color-color diagrams (CCDs) combining the near-infrared (NIR) and mid-infrared (MIR) data to develop a method to…
Convolutional neural nets (CNN) are the leading computer vision method for classifying images. In some cases, it is desirable to classify only a specific region of the image that corresponds to a certain object. Hence, assuming that the…
We are searching for Young Stellar Objects (YSOs) near the boundary between protostars and pre-main sequence objects, what we have termed transitional YSOs. We have identified a sample of 125 objects as candidate transitional YSOs on the…
We present an automatic, fast, accurate and robust method of classifying astronomical objects. The Self Organizing Map (SOM) as an unsupervised Artificial Neural Network (ANN) algorithm is used for classification of stellar spectra of…
Innovation in the ground and space-based instruments has taken us into a new age of spectroscopy, in which a large amount of stellar content is becoming available. So, automatic classification of stellar spectra became subjective in recent…
Spiking Neural Networks (SNNs) are a biologically plausible neural network model with significant advantages in both event-driven processing and spatio-temporal information processing, rendering SNNs an appealing choice for energyefficient…