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

Detecting persons using a 2D LiDAR is a challenging task due to the low information content of 2D range data. To alleviate the problem caused by the sparsity of the LiDAR points, current state-of-the-art methods fuse multiple previous scans…

Object detection is a challenging and popular computer vision problem. The problem is even more challenging in aerial images due to significant variation in scale and viewpoint in a diverse set of object categories. Recently, deep…

The next generation of spectroscopic surveys is expected to provide spectra for hundreds of thousands of white dwarf (WD) candidates in the upcoming years. Currently, spectroscopic classification of white dwarfs is mostly done by visual…

A search of more than 3,000 square degrees of high latitude sky by the Sloan Digital Sky Survey has yielded 251 faint high-latitude carbon stars (FHLCs), the large majority previously uncataloged. We present homogeneous spectroscopy,…

We have conducted a 4030-square-deg near-infrared proper motion survey using multi-epoch data from the Two Micron All-Sky Survey (2MASS). We find 2778 proper motion candidates, 647 of which are not listed in SIMBAD. After comparison to DSS…

We utilize a complete sample of RR Lyrae stars discovered by the QUEST survey using light curves to design selection criteria based on SDSS colors. Thanks to the sensitivity of the u-g color to surface gravity and of g-r color to effective…

We apply a new deep learning technique to detect, classify, and deblend sources in multi-band astronomical images. We train and evaluate the performance of an artificial neural network built on the Mask R-CNN image processing framework, a…

The growing number of man-made debris in Earth's orbit poses a threat to active satellite missions due to the risk of collision. Characterizing unknown debris is, therefore, of high interest. Light Curves (LCs) are temporal variations of…

Context. Euclid will carry out a deep survey benefiting the discovery and characterisation of ultracool dwarfs (UCDs), especially in the Euclid Deep Fields (EDFs), which the telescope will scan repeatedly throughout its mission. The…

Identifying dwarf galaxies within the Local Volume is crucial for constraining the luminosity function of satellite galaxies in the nearby universe. We report the detection capabilities of dwarf galaxies within the Local Volume using the…

SDSS J080531.84+481233.0 is a peculiar L-type dwarf that exhibits unusually blue near-infrared and mid-infrared colors and divergent optical (L4) and near-infrared (L9.5) spectral classifications. These peculiar spectral traits have been…

Surveys for nearby low-luminosity dwarfs tend to avoid the crowded regions of the Galactic Plane. We have devised near-infrared colour-magnitude and colour-colour selection criteria designed to identify late-type M and early-type L dwarfs…

We present a morphological catalogue for $\sim$ 670,000 galaxies in the Sloan Digital Sky Survey in two flavours: T-Type, related to the Hubble sequence, and Galaxy Zoo 2 (GZ2 hereafter) classification scheme. By combining accurate existing…

A novel deep learning paradigm for synthesis imaging by radio interferometry in astronomy was recently proposed, dubbed "Residual-to-Residual DNN series for high-Dynamic range imaging" (R2D2). In this work, we start by shedding light on…

Autonomous digital sky surveys such as Pan-STARRS have the ability to image a very large number of galactic and extra-galactic objects, and the large and complex nature of the image data reinforces the use of automation. Here we describe…

We propose a new type of efficient deep-unrolling networks for solving imaging inverse problems. Conventional deep-unrolling methods require full forward operator and its adjoint across each layer, and hence can be significantly more…

We explore and demonstrate the capabilities of LSST to study Type I superluminous supernovae (SLSNe). We first fit the light curves of 58 known SLSNe at z~0.1-1.6, using an analytical magnetar spin-down model implemented in MOSFiT. We then…

As an emerging technology and a relatively affordable device, the 4D imaging radar has already been confirmed effective in performing 3D object detection in autonomous driving. Nevertheless, the sparsity and noisiness of 4D radar point…

Drone detection has benefited from improvements in deep neural networks, but like many other applications, suffers from the availability of accurate data for training. Synthetic data provides a potential for low-cost data generation and has…

The space density of late M dwarfs, subtypes M7-M9.5, is not well determined. We applied the photo-type method to $iz$ photometry from the Sloan Digital Sky Survey and $YJHK$ photometry from the UKIRT Infrared Deep Sky Survey, over an…