Related papers: Quantifying the fine structures of disk galaxies w…
We have imaged a sample of 45 face-on spiral galaxies in the K-band, to determine the morphology of the old stellar population, which dominates the mass in the disk. The K-band images of the spiral galaxies have been used to calculate…
The interstellar medium has a highly filamentary and hierarchical structure, which may play a significant role in star formation. A systematical study on the large-scale filaments towards their physical parameters, distribution, structures…
Encoder-Decoder networks such as U-Nets have been applied successfully in a wide range of computer vision tasks, especially for image segmentation of different flavours across different fields. Nevertheless, most applications lack of a…
Disks are ubiquitous in stellar astronomy, and play a crucial role in the formation and evolution of stars. In this contribution we present an overview of the most recent results, with emphasis on high spatial and spectral resolution. We…
In this paper, a deep convolutional neural network architecture for galaxies classification is presented. The galaxy can be classified based on its features into main three categories Elliptical, Spiral, and Irregular. The proposed deep…
The goal of this paper is to develop a machine learning model to analyze the main gravitational lens and detect dark substructure (subhalos) within simulated images of strongly lensed galaxies. Using the technique of image segmentation, we…
The classification of galaxies as spirals or ellipticals is a crucial task in understanding their formation and evolution. With the arrival of large-scale astronomical surveys, such as the Sloan Digital Sky Survey (SDSS), astronomers now…
To date, galaxy image simulations for weak lensing surveys usually approximate the light profiles of all galaxies as a single or double S\'ersic profile, neglecting the influence of galaxy substructures and morphologies deviating from such…
Deep imaging is a fundamental tool in the study of the outermost structures of galaxies. We review recent developments in ultra-deep imaging of galaxy disks and haloes, highlighting the technical advances as well as the challenges, and…
In clinical practice, regions of interest in medical imaging often need to be identified through a process of precise image segmentation. The quality of this image segmentation step critically affects the subsequent clinical assessment of…
Deep neural networks (DNNs) with a step-by-step introduction of inputs, which is constructed by imitating the somatosensory system in human body, known as SpinalNet have been implemented in this work on a Galaxy Zoo dataset. The input…
The first mechanism invoked to explain the existence of the thick disk in the Milky Way Galaxy, were the spiral arms. Up-to-date work summon several other possibilities that together seem to better explain this component of our Galaxy. All…
Given an approximately centered image of a spiral galaxy, we describe an entirely automated method that finds, centers, and sizes the galaxy and then automatically extracts structural information about the spiral arms. For each arm segment…
We investigate the use of spiral arm pitch angles as a probe of disk galaxy mass profiles. We confirm our previous result that spiral arm pitch angles (P) are well correlated with the rate of shear (S) in disk galaxy rotation curves. We use…
The development of two-dimensional (2D) bulge-to-disk decomposition techniques has shown their advantages over traditional one-dimensional (1D) techniques, especially for galaxies with non-axisymmetric features. However, the full potential…
Classification of galactic morphologies is a crucial task in galactic astronomy, and identifying fine structures of galaxies (e.g., spiral arms, bars, and clumps) is an essential ingredient in such a classification task. However, seeing…
The Carnegie-Irvine Galaxy Survey provides high-quality broad-band optical images of a large sample of nearby galaxies for detailed study of their structure. To probe the physical nature and possible cosmological evolution of spiral arms, a…
Most existing star-galaxy classifiers use the reduced summary information from catalogs, requiring careful feature extraction and selection. The latest advances in machine learning that use deep convolutional neural networks allow a machine…
Spiral galaxies are observed to exhibit a range of morphologies, in particular in the shape of spiral arms. A key diagnostic parameter is the pitch angle, which describes how tightly wound the spiral arms are. Observationally and…
We test whether the spiral patterns apparent in many large disk galaxies should be thought of as dynamical features that are stationary in a co-rotating frame for > t_{dyn}, as implied by the density wave approach for explaining spiral…