相关论文: Data-Efficient Classification of Radio Galaxies
Radio continuum surveys can detect galaxies over a very wide range in redshift, making them powerful tools for studying the distant universe. Until recently, though, identifying the optical counterparts of faint radio sources and measuring…
Magnetic Resonance Imaging (MRI) is a principal diagnostic approach used in the field of radiology to create images of the anatomical and physiological structure of patients. MRI is the prevalent medical imaging practice to find…
Detecting anomalies in radio astronomy is challenging due to the vast amounts of data and the rarity of labeled anomalous examples. Addressing this challenge requires efficient methods capable of identifying unusual radio galaxy…
The superb sensitivity and angular resolution of the next-generation radio telescopes with combined frequency coverage of approximately over three orders of magnitude (100 MHz--100 GHz) will sample the radio and far-infrared (FIR) spectral…
We present an unsupervised machine learning technique that automatically segments and labels galaxies in astronomical imaging surveys using only pixel data. Distinct from previous unsupervised machine learning approaches used in astronomy…
We present a classification of galaxies in the Pan-STARRS1 (PS1) 3$\pi$ survey based on their recent star formation history and morphology. Specifically, we train and test two Random Forest (RF) classifiers using photometric features…
The classification of galaxy morphology is a hot issue in astronomical research. Although significant progress has been made in the last decade in classifying galaxy morphology using deep learning technology, there are still some…
Galaxy morphology reflects structural properties which contribute to understand the formation and evolution of galaxies. Deep convolutional networks have proven to be very successful in learning hidden features that allow for unprecedented…
We present a catalog of 47 wide-angle tailed radio galaxies (WATs), the WATCAT; these galaxies were selected by combining observations from the National Radio Astronomy Observatory/Very Large Array Sky Survey (NVSS), the Faint Images of the…
Using spectral tomography to separate overlapping spectral features in a sample of FRII radio galaxies, we find a variety of spatial/spectral features that are not easily described in the context of current models. In particular, we find…
Understanding the formation and evolution of ring galaxies, which possess an atypical ring-like structure, is crucial for advancing knowledge of black holes and galaxy dynamics. However, current catalogs of ring galaxies are limited, as…
In this work we explore the possibility of applying machine learning methods designed for one-dimensional problems to the task of galaxy image classification. The algorithms used for image classification typically rely on multiple costly…
This work shows how human physical reasoning can guide machine-driven symbolic regression toward discovering empirical laws from observations. As an example, we derive a simple equation that classifies fast radio bursts (FRBs) into two…
Basing our analysis on ROGUE I, a catalog of over 32,000 radio sources associated with optical galaxies, we provide two diagnostics to select the galaxies where the radio emission is due to an active galactic nucleus (AGN). Each of these…
Modern large radio continuum surveys have high sensitivity and resolution, and can resolve previously undetected extended and diffuse emissions, which brings great challenges for the detection and morphological classification of extended…
Pattern recognition techniques have been used with increasing success for coping with the tremendous amounts of data being generated by automated surveys. Usually this process involves construction of training sets, the typical examples of…
A new class of low-power compact radio sources with limited jet structures, named FR0, is emerging from recent radio-optical surveys. This abundant population of radio galaxies, five times more numerous than FRIs in the local Universe…
We are conducting a large survey of distant clusters of galaxies using radio sources with bent jets and lobes as tracers. These radio sources are driven by AGN and achieve their bent morphologies through interaction with the surrounding gas…
Cross-matching catalogues from radio surveys to catalogues of sources at other wavelengths is extremely hard, because radio sources are often extended, often consist of several spatially separated components, and often no radio component is…
Spectrum sensing is a key technology for cognitive radios. We present spectrum sensing as a classification problem and propose a sensing method based on deep learning classification. We normalize the received signal power to overcome the…