Related papers: Multiband galaxy morphologies for CLASH: a convolu…

We present the first weak gravitational lensing analysis of the completed Canada-France-Hawaii Telescope Legacy Survey (CFHTLS). We study the 64 square degrees W1 field, the largest of the CFHTLS-Wide survey fields, and present the largest…

We present the results from a new search for candidate galaxies at z ~ 8.5-11 discovered over the 850 arcmin^2 area probed by the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS). We use a photometric redshift…

In this paper, a deep convolutional neural network architecture for galaxies classification is presented. The galaxy can be classified based on its features into main three categories Elliptical, Spiral, and Irregular. The proposed deep…

Classification of galaxies is traditionally associated with their morphologies through visual inspection of images. The amount of data to come renders this task inhuman and Machine Learning (mainly Deep Learning) has been called to the…

The two-step galaxy morphology classification framework {\tt USmorph} successfully combines unsupervised machine learning (UML) with supervised machine learning (SML) methods. To enhance the UML step, we employed a dual-encoder architecture…

The universe is composed of galaxies that have diverse shapes. Once the structure of a galaxy is determined, it is possible to obtain important information about its formation and evolution. Morphologically classifying galaxies means…

We present the galaxy-galaxy angular correlations as a function of photometric redshift in a deep-wide galaxy survey centered on the Hubble Deep Field South. Images were obtained with the Big Throughput Camera on the Blanco 4m telescope at…

We report an automated morphological classification of galaxies into S-wise spirals, Z-wise spirals, and non-spirals using big image data taken from Subaru/Hyper Suprime-Cam (HSC) Survey and a convolutional neural network(CNN)-based deep…

We present a description of the observations and data reduction procedures for an extensive spectroscopic and multi-band photometric study of nine high redshift, optically-selected cluster candidates. The primary goal of the survey is to…

Context. Convolutional neural networks (CNNs) are widely used for automated galaxy morphological classification in large surveys. However, projection effects, image artefacts, and intrinsic degeneracies limit reliable identification of…

This work is focused on the morphological classification of galaxies following the Hubble sequence in which the different classes are arranged in a hierarchy. The proposed method, BCNN, is composed of two main modules. First, a…

The new generation of deep photometric surveys requires unprecedentedly precise shape and photometry measurements of billions of galaxies to achieve their main science goals. At such depths, one major limiting factor is the blending of…

The galaxy cluster MACS J0717.5+3745 (z=0.55) is the largest known cosmic lens, with complex internal structures seen in deep X-ray, Sunyaev-Zel'dovich effect and dynamical observations. We perform a combined weak and strong lensing…

We examine a general framework for visualizing datasets of high (> 2) dimensionality, and demonstrate it using the morphology of galaxies at moderate redshifts. The distributions of various populations of such galaxies are examined in a…

We propose a variant of residual networks (ResNets) for galaxy morphology classification. The variant, together with other popular convolutional neural networks (CNNs), are applied to a sample of 28790 galaxy images from Galaxy Zoo 2…

We present a selection of 24 candidate galaxy-galaxy lensing (GGLs) identified from Hubble images in the outskirts of the massive galaxy clusters from the CLASH survey. These GGLs provide insights into the mass distributions at larger…

We use multi-band optical and near-infrared photometric observations of galaxies in the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS) to predict photometric redshifts using artificial neural networks. The…

The UltraViolet imaging of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey Fields (UVCANDELS) program provides deep HST F275W and F435W imaging over four CANDELS fields (GOODS-N, GOODS-S, COSMOS, and EGS). We combine this…

We have carried out a systematic search for galaxy-scale strong lenses in multiband imaging from the Hyper Suprime-Cam (HSC) survey. Our automated pipeline, based on realistic strong-lens simulations, deep neural network classification, and…

We present the KMOS-CLASH (K-CLASH) survey, a K-band Multi-Object Spectrograph (KMOS) survey of the spatially-resolved gas properties and kinematics of 191 (predominantly blue) H$\alpha$-detected galaxies at $0.2 \lesssim z \lesssim 0.6$ in…