Related papers: L dwarfs detection from SDSS images using improved…

We conducted a search for brown dwarf candidates in a James Webb Space Telescope deep field around A2744 to investigate the space density of these objects at kiloparsec distances. Our methodology employed an initial selection based on…

High-redshift quasars are important tracers of structure and evolution in the early universe. However, they are very rare and difficult to find when using color selection because of contamination from late-type dwarfs. High-redshift quasar…

We present the discovery of 118 new ultracool dwarf candidates, discovered using a new machine learning tool, named \texttt{SMDET}, applied to time series images from the Wide-field Infrared Survey Explorer. We gathered photometric and…

With the advent of modern expert systems driven by deep learning that supplement human experts (e.g. radiologists, dermatologists, surveillance scanners), we analyze how and when do such expert systems enhance human performance in a…

Thanks to incredible advances in instrumentation, surveys like the Sloan Digital Sky Survey have been able to find and catalog billions of objects, ranging from local M dwarfs to distant quasars. Machine learning algorithms have greatly…

With the demand for standardized large-scale livestock farming and the development of artificial intelligence technology, a lot of research in area of animal face recognition were carried on pigs, cattle, sheep and other livestock. Face…

Lymph node (LN) assessment is a critical, indispensable yet very challenging task in the routine clinical workflow of radiology and oncology. Accurate LN analysis is essential for cancer diagnosis, staging, and treatment planning. Finding…

We present the discovery of two new late-T dwarfs identified in the UKIRT Infrared Deep Sky Survey (UKIDSS) Galactic Clusters Survey (GCS) Data Release 2 (DR2). These T dwarfs are nearby old T dwarfs along the line of sight to star-forming…

Deep Learning (DL) algorithms for morphological classification of galaxies have proven very successful, mimicking (or even improving) visual classifications. However, these algorithms rely on large training samples of labelled galaxies…

Starting from a summary of detection statistics of our recent X-shooter campaign, we review the major surveys, both space and ground based, for emission counterparts of high-redshift damped Ly$\alpha$ absorbers (DLAs) carried out since the…

We present an approach to identifying and characterizing unresolved, very low mass spectral blend binaries composed of late-M, L, and T dwarfs using machine learning methodologies. We generated and evaluated a series of hierarchical random…

This paper studies the problem of Line Segment Detection (LSD) for the characterization of line geometry in images, with the aim of learning a domain-agnostic robust LSD model that works well for any natural images. With the focus of…

The Sloan Digital Sky Survey (SDSS) will carry out a digital photometric and spectroscopic survey over pi steradians in the northern Galactic cap. An array of CCD detectors used in drift-scan mode will image the sky in five passbands to a…

Robust data association is necessary for virtually every SLAM system and finding corresponding points is typically a preprocessing step for scan alignment algorithms. Traditionally, handcrafted feature descriptors were used for these…

State-of-the-art object detection approaches such as Fast/Faster R-CNN, SSD, or YOLO have difficulties detecting dense, small targets with arbitrary orientation in large aerial images. The main reason is that using interpolation to align…

We present the second report of our systematic search for strongly lensed quasars from the data of the Sloan Digital Sky Survey (SDSS). From extensive follow-up observations of 136 candidate objects, we find 36 lenses in the full sample of…

The Sloan Digital Sky Survey (SDSS) is a project to definitively map $\pi$ steradians of the local Universe. An array of CCD detectors used in drift-scan mode will digitally image the sky in five passbands to a limiting magnitude of $r'…

We report the discovery of a second field methane brown dwarf from the commissioning data of the Sloan Digital Sky Survey (SDSS). The object, SDSS J134646.45-003150.4 (SDSS 1346-00), was selected because of its very red color and stellar…

Traditional photometric redshift methods use only color information about the objects in question to estimate their redshifts. This paper introduces a new method utilizing colors, luminosity, surface brightness, and radial light profile to…

In this paper we present a two-step neural network model to separate detections of solar system objects from optical and electronic artifacts in data obtained with the "Asteroid Terrestrial-impact Last Alert System" (ATLAS), a near-Earth…