Related papers: YOLO-CL: Galaxy cluster detection in the SDSS with…
Colorectal cancer (CRC), a lethal disease, begins with the growth of abnormal mucosal cell proliferation called polyps in the inner wall of the colon. When left undetected, polyps can become malignant tumors. Colonoscopy is the standard…
In recent decades, large-scale sky surveys such as Sloan Digital Sky Survey (SDSS) have resulted in generation of tremendous amount of data. The classification of this enormous amount of data by astronomers is time consuming. To simplify…
Galaxy cluster-scale strong gravitational lensing systems are rare yet valuable tools for investigating the properties of dark matter and dark energy, as well as providing the opportunity to study the distant universe at flux levels and…
Galaxy clusters enable unique opportunities to study cosmology, dark matter, galaxy evolution, and strongly-lensed transients. We here present a new cluster-finding algorithm, CluMPR (Clusters from Masses and Photometric Redshifts), that…
We develop a galaxy cluster finding algorithm based on spectral clustering technique to identify optical counterparts and estimate optical redshifts for X-ray selected cluster candidates. As an application, we run our algorithm on a sample…
We present a new algorithm to search for distant clusters of galaxies on catalogues deriving from imaging data, as those of the ESO Imaging Survey. Our algorithm is a matched filter one, similar to that adopted by Postman et al. (1996),…
We present a deep machine learning (ML) approach to constraining cosmological parameters with multi-wavelength observations of galaxy clusters. The ML approach has two components: an encoder that builds a compressed representation of each…
With an excellent balance between speed and accuracy, cutting-edge YOLO frameworks have become one of the most efficient algorithms for object detection. However, the performance of using YOLO networks is scarcely investigated in brain…
The sensitivity and wide area reached by ongoing and future wide-field optical surveys allows for the detection of an increasing number of galaxy clusters uniquely through their weak lensing (WL) signal. This motivates the development of…
Galaxy-scale strong lenses in galaxy clusters provide a unique tool to investigate their inner mass distribution and the sub-halo density profiles in the low-mass regime, which can be compared with the predictions from cosmological…
Complete blood cell detection holds significant value in clinical diagnostics. Conventional manual microscopy methods suffer from time inefficiency and diagnostic inaccuracies. Existing automated detection approaches remain constrained by…
Taking advantage of $\sim4700$ deg$^2$ optical coverage of the Southern sky offered by the VST ATLAS survey, we construct a new catalogue of photometrically selected galaxy groups and clusters using the {\sc orca} cluster detection…
The Northern Sky Optical Cluster Survey is a project to create an objective catalog of galaxy clusters over the entire high-galactic-latitude Northern sky, with well understood selection criteria. We use the object catalogs generated from…
We present an optimised galaxy cluster finder, 3D-Matched-Filter (3D-MF), which utilises galaxy cluster radial profiles, luminosity functions and redshift information to detect galaxy clusters in optical surveys. This method is an…
The upcoming XMM Large Scale Structure Survey (XMM-LSS) will ultimately provide a unique mapping of the distribution of X-ray sources in a contiguous 64 sq. deg. region. In particular, it will provide the 3-dimensional location of about 900…
We describe the scientific motivation behind, and the methodology of, the Stanford Cluster Search (StaCS), a program to compile a catalog of optically selected clusters of galaxies at intermediate and high (0.3 < z < 1) redshifts. The…
We construct a large, redshift complete sample of distant galaxy clusters by correlating Sloan Digital Sky Survey (SDSS) Data Release 12 (DR12) redshifts with clusters identified with the red-sequence Matched-filter Probabilistic…
Edge-on galaxies have many important applications in galactic astrophysics, but they can be difficult to identify in vast amounts of astronomical data. To facilitate the search for them, we have developed a deep learning algorithm designed…
I review here past and present research on clusters and groups of galaxies within the Sloan Digital Sky Survey (SDSS). In particular, I discuss the C4 algorithm which is designed to search for clusters within a 7-dimensional data-space,…
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…