Related papers: Identifying bars in galaxies using machine learnin…
Understanding the methodological robustness in identifying and quantifying high-redshift bars is essential for studying their evolution with the {\it James} {\it Webb} Space Telescope (JWST). We used nearby spiral galaxies to generate…
Almost two-thirds of disk galaxies in the local universe host bars, which serve as important drivers of secular evolutionary processes. While cosmological simulations are powerful tools to study the formation and evolution of galaxies, they…
We present surface photometry and stellar kinematics of a sample of 5 SB0 galaxies: ESO 139-G009, IC 874, NGC 1308, NGC 1440 and NGC 3412. We measured their bar pattern speed using the Tremaine-Weinberg method, and derived the ratio, R, of…
In this work we determine the parameters of spiral structure for a sample of face-on spiral galaxies. In practice, the solution of this problem is a hard task because of the diversity of the observed characteristics of spiral structure,…
In this paper we use the two-dimensional (2D) version of a new analytical gravitational model in order to explore the orbital as well as the escape dynamics of the stars in a barred galaxy composed of a spherically symmetric central…
The pattern speed in one of the fundamental parameters that determines the structure of barred galaxies. This quantity is usually derived from indirect methods or by employing model assumptions. The number of bar pattern speeds derived…
This research paper presents an innovative ship detection system tailored for applications like maritime surveillance and ecological monitoring. The study employs YOLOv8 and repurposed U-Net, two advanced deep learning models, to…
In this work we analyse the structural and photometric properties of 21 barred simulated galaxies from the Auriga Project. These consist of Milky Way-mass magneto-hydrodynamical simulations in a $\Lambda$CDM cosmological context. In order…
The division of galaxies into ``barred'' (SB) and ``normal'' (S) spirals is a fundamental aspect of the Hubble galaxy classification system. This ``tuning fork'' view was revised by de Vaucouleurs, whose classification volume recognized…
Modern leading object detectors are either two-stage or one-stage networks repurposed from a deep CNN-based backbone classifier network. YOLOv3 is one such very-well known state-of-the-art one-shot detector that takes in an input image and…
We investigate how the environment of a dynamically unrelaxed galaxy cluster influences the structure and dynamics of stellar bars. In particular, we examine cluster-centric variations in normalised bar size and bar pattern speed in Abell…
Open-vocabulary detection (OVD) aims to detect objects beyond a predefined set of categories. As a pioneering model incorporating the YOLO series into OVD, YOLO-World is well-suited for scenarios prioritizing speed and efficiency. However,…
I present results from the modeling of stellar bars in nearly 300 barred galaxies in the local universe through parametric multi-component multi-band image fitting. The surface brightness radial profile of bars is described using a Sersic…
Accurate measurements of statistical properties, such as the star formation rate and the lifetime of young stellar objects (YSOs) in different stages, is essential for constraining star formation theories. However, it is a difficult task to…
Recent years have witnessed the advancement of deep learning vision technologies and applications in the medical industry. Intelligent devices for special medication management are in great need of, which requires more precise detection…
The results of morphological galaxy classifications performed by humans and by automated methods are compared. In particular, a comparison is made between the eyeball classifications of 454 galaxies in the Sloan Digital Sky Survey (SDSS)…
Artificial intelligence-enhanced identification of organs, lesions, and other structures in medical imaging is typically done using convolutional neural networks (CNNs) designed to make voxel-accurate segmentations of the region of…
This paper describes a framework for studying galaxy morphology, particularly bar strength, in a quantitative manner, and presents applications of this approach that reveal observational evidence for secular evolution in bar morphology. The…
This paper presents machine learning experiments performed over results of galaxy classification into elliptical (E) and spiral (S) with morphological parameters: concetration (CN), assimetry metrics (A3), smoothness metrics (S3), entropy…
In order to obtain morphological information of unlabeled galaxies, we present an unsupervised machine-learning (UML) method for morphological classification of galaxies, which can be summarized as two aspects: (1) the methodology of…