An application of deep learning in the analysis of stellar spectra

Here, we apply a deep neural network architecture to analyse both SDSS-III APOGEE DR13 and synthetic stellar spectra.

An Application of Deep Neural Networks in the Analysis of Stellar ...

Here we apply a deep neural network architecture to analyze both SDSS-III APOGEE DR13 and synthetic stellar spectra.

StarNet: An application of deep learning in the analysis of stellar ...

StarNet: An application of deep learning in the analysis of stellar spectra ... Abstract. In an era when spectroscopic surveys are capable of collecting spectra ...

An application of deep learning in the analysis of stellar spectra

Request PDF | An application of deep learning in the analysis of stellar spectra | Spectroscopic surveys require fast and efficient analysis methods to ...

An application of deep learning in the analysis of stellar spectra

When our convolutional neural network model (StarNet) is trained on APOGEE spectra, we show that the stellar parameters (temperature, gravity, ...

(PDF) The use of Deep Learning in stellar classification

PDF | We are applying various ML/DL techniques for the purpose of stellar spectroscopy. Having already ran tests with Principal Component Analysis (PCA).

Deep Learning application for stellar parameters determination - arXiv

In this study, we show, a pedagogical approach that should benefit anyone willing to experiment with Deep Learning techniques in the context of stellar ...

Application of convolutional neural networks for stellar spectral ...

However, deep learning methods with a larger number of hidden layers allow the use ... methods: data analysis;; techniques: spectroscopic;; catalogues;; stars ...

Deep learning application for stellar parameters determination

... stellar parameters but what is the effect of specific parameters on stellar spectra analysis. By applying our models to A stars, we use previous results ...

‪Spencer Bialek‬ - ‪Google Scholar‬

An application of deep learning in the analysis of stellar spectra S Fabbro, KA Venn, T O'Briain, S Bialek, CL Kielty, F Jahandar, S Monty

SUPPNet: Neural network for stellar spectrum normalisation

... spectra and offers flexible manual fine-tuning, if necessary. Methods. The core of the proposed method uses the novel, fully convolutional deep neural network ...

Stellar parameter estimation in O-type stars using artificial neural ...

This work presents the results of the implementation of a deep learning ... stellar spectra using modern deep-learning techniques. In the artificial ...

Generating Stellar Spectra Using Neural Networks - MDPI

... uses Deep Learning to reconstruct stellar spectra based on a set of stellar parameters ... analysis of the generated spectra in order to constrain their use ...

A Blended Artificial Intelligence Approach for Spectral Classification ...

Application of convolutional neural networks for stellar spectral classification. ... stellar spectra based on deep convolutional neural network. Mon. Not. R ...

StarNet: a deep learning analysis of infrared stellar spectra

Remaining challenges in our StarNet applications include rectification, continuum normalization, and wavelength coverage. Here with present ...

Application of convolutional neural networks for stellar spectral ...

An application of deep learning in the analysis of stellar spectra · S. FabbroK. Venn +4 authors. S. Monty. Physics, Computer Science. 2018. TLDR. A deep neural ...

Machine Learning for Stellar Spectra - DiVA portal

This section discusses the background of stars and stellar spectra. Some previous work done within machine learning applications in astronomy is discussed in ...

Estimation of Physical Stellar Parameters from Spectral Models ...

data analysis; deep learning; massive stars ... Deep learning application for stellar parameters determination: I-constraining the hyperparameters.

The impact of deep learning for the analysis of galaxy surveys

methods that use SDSS spectra which are more time consum- ing to obtain. ... The star symbol highlights applications which require simulations to train the neural ...

"Classification of Stars from Redshifted Stellar Spectra utilizing Mach ...

A physical phenomenon known as redshift causes machine learning complications through the feature matrix when classifying stellar spectra.