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Radio Galaxy Zoo: Giant Radio Galaxy Classification using Multi-Domain Deep Learning [article]

H.Tang, A.M.M.Scaife, O.I.Wong, S.S.Shabala
2021 arXiv   pre-print
In this work, we explore the potential of multi-domain multi-branch convolutional neural networks (CNNs) for identifying comparatively rare giant radio galaxies from large volumes of survey data, such  ...  We find that the inclusion of multi-resolution survey data results in correction of 39% of the misclassifications seen from equivalent single domain networks for the classification problem considered in  ...  ACKNOWLEDGEMENTS The authors are grateful for the assistance of over 12,000 volunteers in the Radio Galaxy Zoo project, whose contributions are acknowledged at http://rgzauthors.galaxyzoo.org.  ... 
arXiv:2112.03564v1 fatcat:t44quewy65dqxia7vyc6xxtvdy

The Brazilian Virtual Observatory - A New Paradigm for Astronomy

R. Carvalho
2010 Journal of Computational Interdisciplinary Sciences  
The VO is a response to the astronomical community's demands for improved and homogenized access to these data, combined with the tools to manipulate and explore them.  ...  For classifying an object, the starting point is the root of the tree; a test is applied to one attribute and the appropriate output branch is determined.  ...  Considerable attention has been paid to morphological classification of E/SO/Sa/Sab/Sm/Irr galaxy morphologies using Sloan Digital Sky Survey imaging.  ... 
doi:10.6062/jcis.2010.01.03.0022 fatcat:wsakyvdypvcmvg2cjjt6mjwoji

Estimating Cluster Masses from SDSS Multi-band Images with Transfer Learning [article]

Sheng-Chieh Lin, Yuanyuan Su, Gongbo Liang, Yuanyuan Zhang, Nathan Jacobs, Yu Zhang
2022 arXiv   pre-print
It is crucial to obtain reliable and accurate mass estimates for numerous galaxy clusters over a wide range of redshifts and mass scales.  ...  The total masses of galaxy clusters characterize many aspects of astrophysics and the underlying cosmology.  ...  Multi-wavelength observations have been utilized to probe the total masses of galaxy clusters.  ... 
arXiv:2203.06288v1 fatcat:mnppniemdja7pnrzlexzj24vum

SExtractor: Software for source extraction

E. Bertin, S. Arnouts
1996 Astronomy and Astrophysics Supplement Series  
We show that a very reliable star/galaxy separation can be achieved on most images using a neural network trained with simulated images.  ...  We present the automated techniques we have developed for new software that optimally detects, deblends, measures and classifies sources from astronomical images: SExtractor (Source Extractor ).  ...  We thank all the users of the beta-version of SExtractor for their comments and suggestions, P. Fouqué and C.Lidman for comments on the manuscript of this paper.  ... 
doi:10.1051/aas:1996164 fatcat:iqbmxgk5urfyppwwn4ocrowkui

Surveying the reach and maturity of machine learning and artificial intelligence in astronomy

Christopher J. Fluke, Colin Jacobs
2019 Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery  
Random forests, support vector machines, and neural networks (artificial, deep, and convolutional) are now having a genuine impact for applications as diverse as discovering extrasolar planets, transient  ...  Applications span seven main categories of activity: classification, regression, clustering, forecasting, generation, discovery, and the development of new scientific insight.  ...  The reference point for many of the automated classifiers is the work done by human volunteers for projects like Galaxy Zoo [Lintott et al., 2008] .  ... 
doi:10.1002/widm.1349 fatcat:k7swo7ozu5hhljtjlzofkxhb7u

Scientific Data Mining in Astronomy [article]

Kirk Borne
2009 arXiv   pre-print
We posit that data mining has always been fundamental to astronomical research, since data mining is the basis of evidence-based discovery, including classification, clustering, and novelty discovery.  ...  Astroinformatics is described as both a research approach and an educational imperative for modern data-intensive astronomy.  ...  Two other problems that have received a lot of astronomical research attention using neural networks are: (a) the classification of different galaxy types within large databases of galaxy data (e.g.,  ... 
arXiv:0911.0505v1 fatcat:6hevyivrvfcobb6estoomsxafy

Mapping and characterisation of cosmic filaments in galaxy cluster outskirts: strategies and forecasts for observations from simulations [article]

Ulrike Kuchner, Alfonso Aragón-Salamanca, Frazer R. Pearce, Meghan E. Gray, Agustín Rost, Chunliang Mu, Charlotte Welker, Weiguang Cui, Roan Haggar, Clotilde Laigle, Alexander Knebe, Katarina Kraljic (+2 others)
2020 arXiv   pre-print
Encouragingly, the overall 3-dimensional filament networks and∼67associated with them are recovered from 2-dimensional galaxy positions.  ...  Upcoming wide-field surveys are well-suited to studying the growth of galaxy clusters by tracing galaxy and gas accretion along cosmic filaments.  ...  classified as galaxies in filaments).  ... 
arXiv:2004.08408v1 fatcat:7fvocvarkfhfvlhsh2hamvqng4

PHANGS-HST: New Methods for Star Cluster Identification in Nearby Galaxies [article]

David A. Thilker, Bradley C. Whitmore, Janice C. Lee, Sinan Deger, Rupali Chandar, Kirsten L. Larson, Stephen Hannon, Leonardo Ubeda, Daniel A. Dale, Simon C. O. Glover, Kathryn Grasha, Ralf S. Klessen (+5 others)
2021 arXiv   pre-print
spiral galaxies.  ...  We quantify the performance of our PHANGS-HST methods in comparison to LEGUS for a sample of four galaxies in common to both surveys, finding overall agreement with 50-75% of human verified star clusters  ...  SCOG and RSK acknowledge support from the DFG via SFB 881 "The Milky Way System" (sub-projects A1, B1, B2 and B8) and from the Heidelberg cluster of excellence EXC 2181-390900948 "STRUCTURES: A unifying  ... 
arXiv:2106.13366v2 fatcat:rdzvgu2xifcc3bw7b6pfp4dory

ArborZ: PHOTOMETRIC REDSHIFTS USING BOOSTED DECISION TREES

David W. Gerdes, Adam J. Sypniewski, Timothy A. McKay, Jiangang Hao, Matthew R. Weis, Risa H. Wechsler, Michael T. Busha
2010 Astrophysical Journal  
provides a photo-z quality figure-of-merit for each galaxy that can be used to reject outliers.  ...  Moreover, the method naturally leads to the reconstruction of a full probability density function (PDF) for the photometric redshift of each galaxy, not merely a single "best estimate" and error, and also  ...  Each bin is assigned its own BDT classifier. The N galaxies whose redshifts fall into bin i form the "signal" training set for the ith classifier.  ... 
doi:10.1088/0004-637x/715/2/823 fatcat:p7ysg4xlezb5tcbvpz7xknarra

SPIDER – IX. Classifying galaxy groups according to their velocity distribution

A. L. B. Ribeiro, R. R. de Carvalho, M. Trevisan, H. V. Capelato, F. La Barbera, P. A. A. Lopes, A. C. Schilling
2013 Monthly notices of the Royal Astronomical Society  
For the Berlind group sample (z<0.1), 67% of the systems are classified as relaxed, while for the Millennium sample we find 63% (z=0).  ...  We introduce a new method to study the velocity distribution of galaxy systems, the Hellinger Distance (HD) - designed for detecting departures from a Gaussian velocity distribution.  ...  Einasto for important suggestions. We also thank B. Carvalho for helpful discussions on statistics.  ... 
doi:10.1093/mnras/stt1071 fatcat:gudpaebvrfce5mgsumjjfjvsdq

Can We `Feel' the Temperature of Knowledge? Modelling Scientific Popularity Dynamics via Thermodynamics [article]

Luoyi Fu, Dongrui Lu, Qi Li, Xinbing Wang, Chenghu Zhou
2020 arXiv   pre-print
Here, we conceive knowledge temperature to quantify topic overall popularity and impact through citation network dynamics. Knowledge temperature includes 2 parts.  ...  While existing literature well captures article's life-cycle via citation patterns, little is known about how scientific popularity and impact evolves for a specific topic.  ...  For example, paper 'Combatting maelstroms in networks of communicating agents' published in 1999 connects the entire left research branch and the central cluster led by the pioneering work.  ... 
arXiv:2007.13270v1 fatcat:qybvondcsfg2fh7gb2goxfwvnm

Large scale structure in the SDSS galaxy survey

A. Doroshkevich, D. L. Tucker, S. Allam, M. J. Way
2004 Astronomy and Astrophysics  
The measured characteristics of galaxy walls were found to be consistent with those for a spatially flat ΛCDM cosmological model with Ω_m≈ 0.3 and Ω_Λ≈ 0.7, and for Gaussian initial perturbations with  ...  Using the Minimal Spanning Tree technique we have extracted sets of filaments, of wall-like structures, of galaxy groups, and of rich clusters from this unique sample.  ...  The Participating Institutions are the University of Chicago, Fermilab, the Institute for Advanced Study, the Japan Participation Group, the Johns Hopkins University, the Max Planck Institute for Astronomy  ... 
doi:10.1051/0004-6361:20031780 fatcat:lxwvc7iuozc5hbto6ouu77x74y

Exploring the distribution regularities of user attention and sentiment toward product aspects in online reviews

Chenglei Qin, Chengzhi Zhang, Yi Bu
2021 Electronic library  
Design/methodology/approach Temporal characteristics of online reviews (purchase time, review time and time intervals between purchase time and review time), similar attributes clustering and attribute-level  ...  Research limitations/implications This paper cannot acquire online reviews for more products with temporal characteristics to verify the findings because of the restriction on reviews crawling by the shopping  ...  In this branch of research, Cheng et al. (2017) used hierarchical attention networks to allocate appropriate sentiment words for given product attributes.  ... 
doi:10.1108/el-11-2020-0324 fatcat:qvjvi6ycbbfeziznp6wwtfauay

Challenges for Dark Energy Science: Color Gradients and Blended Objects

Sowmya Kamath
2020 Zenodo  
The expected bias is estimated for the LSST using simulations of parametric galaxies and realistic galaxy images.  ...  The second part of the thesis focuses on the blending challenge for the LSST where a significant fraction of the lensed galaxy images will overlap with images of other objects, affecting the accuracy of  ...  Classification branch The classification branch consists of a fully connected layer followed by a softmax layer (see Equation 5.8) that predicts two scores denoting the confidence of the network in classifying  ... 
doi:10.5281/zenodo.3721437 fatcat:kpllaxbtjrdpdpzwcg2yh4qsey

Astronomy in the Big Data Era

Yanxia Zhang, Yongheng Zhao
2015 Data Science Journal  
in multi-band, and the multi-epoch sky survey.  ...  Edwards and Gaber ( 2014 ) wrote a book titled “Astronomy and Big Data”, which describes a data clustering approach to identifying uncertain galaxy morphology.  ... 
doi:10.5334/dsj-2015-011 fatcat:ufes5d3ng5bnvkyeprznbjzjwa
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