Related papers: Source finding, parametrization and classification…
A significant amount of search queries originate from some real world information need or tasks. In order to improve the search experience of the end users, it is important to have accurate representations of tasks. As a result, significant…
We present a pilot study of extragalactic HI 21-cm absorption lines using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). We observed 5 continuum sources with HI absorption features firstly identified in the 40% data…
We present SoFiA 2, the fully automated 3D source finding pipeline for the WALLABY extragalactic HI survey with the Australian SKA Pathfinder (ASKAP). SoFiA 2 is a reimplementation of parts of the original SoFiA pipeline in the C…
In this paper, we investigate the impact of survey strategy on the performance of self-calibration when the goal is to produce accurate photometric catalogs from wide-field imaging surveys. This self-calibration technique utilizes multiple…
We present an overview of unbiased studies of diffuse extragalactic radio sources. We use a previously developed filtering technique to remove compact sources from large surveys such as WENSS, WISH, and NVSS and examine the residual diffuse…
From May to July 2004, the central radian of the Galactic Plane was scanned by the H.E.S.S. (High Energy Stereoscopic System) telescopes at energies above 200 GeV. This survey was performed from -$3^o$ to +$3^o$ in latitude, for a total of…
Aligning sentences in a reference summary with their counterparts in source documents was shown as a useful auxiliary summarization task, notably for generating training data for salience detection. Despite its assessed utility, the…
The morphologies of astronomical sources are highly complex, making it essential not only to classify the identified sources into their predefined categories but also to determine the sources that are most similar to a given query source.…
Machine learning is now used in many areas of astrophysics, from detecting exoplanets in Kepler transit signals to removing telescope systematics. Recent work demonstrated the potential of using machine learning algorithms for atmospheric…
We present a comparison between the performance of a selection of source finders using a new software tool called Hydra. The companion paper, Paper~I, introduced the Hydra tool and demonstrated its performance using simulated data. Here we…
Radio source detection through conventional algorithms has been unreliable when trying to solve for large number of sources in the presence of low SINR and less number of snapshots. We address this by reformulating source detection as a…
We analyze the distribution of galaxy HI masses detected in a large, deep HI survey conducted at the Arecibo observatory, and we find possible evidence of a faint-end steepening of the mass function similar to what has been found optically.…
We present the first results of our dedicated programme of automatised classification of galaxies, stars and quasars in the mid-infrared all-sky data from the WISE survey. We employ the Support Vector Machines (SVM) algorithm, which defines…
Survey sampling plays an important role in the efficient allocation and management of resources. The essence of survey sampling lies in acquiring a sample of data points from a population and subsequently using this sample to estimate the…
As several large single-dish radio surveys begin operation within the coming decade, a wealth of radio data will become available and provide a new window to the Universe. In order to fully exploit the potential of these data sets, it is…
Motivated by the desire to generate labels for real-time data we develop a method to estimate the dependency structure and accuracy of weak supervision sources incrementally. Our method first estimates the dependency structure associated…
We use machine learning to classify galaxies according to their HI content, based on both their optical photometry and environmental properties. The data used for our analyses are the outputs in the range $z = 0-1$ from MUFASA cosmological…
Signal-background classification is a central problem in High-Energy Physics (HEP), that plays a major role for the discovery of new fundamental particles. A recent method -- the Parametric Neural Network (pNN) -- leverages multiple signal…
Finding and classifying astronomical sources is key in the scientific exploitation of radio surveys. Source-finding usually involves identifying the parts of an image belonging to an astronomical source, against some estimated background.…
The Hierarchical Inference (HI) paradigm employs a tiered processing: the inference from simple data samples are accepted at the end device, while complex data samples are offloaded to the central servers. HI has recently emerged as an…