19 citations · 34 across the 2 of their papers we have counts for
7 papers
Stellar Spectral Interpolation using Machine Learning
Kaushal Sharma, Harinder P. Singh, Ranjan Gupta +6
Theoretical stellar spectra rely on model stellar atmospheres computed based on our understanding of the physical laws at play in the stellar interiors. These models, coupled with…
Application of Convolutional Neural Networks for Stellar Spectral Classification
Kaushal Sharma, Ajit Kembhavi, Aniruddha Kembhavi +3
Due to the ever-expanding volume of observed spectroscopic data from surveys such as SDSS and LAMOST, it has become important to apply artificial intelligence (AI) techniques for a…
A Long-term photometric variability and spectroscopic study of luminous blue variable AF And in M31
Yogesh C. Joshi, Kaushal Sharma, Anjasha Gangopadhyay +2
We present photometric and spectroscopic analysis of the Hubble Sandage variable AF And in M31. The data has been taken under the Nainital Microlensing Survey during 1998-2002 and…
Multiwavelength Period-Luminosity and Period-Luminosity-Color relations at maximum-light for Mira variables in the Magellanic Clouds
Anupam Bhardwaj, Shashi Kanbur, Shiyuan He +8
We present Period-Luminosity and Period-Luminosity-Color relations at maximum-light for Mira variables in the Magellanic Clouds using time-series data from the Optical Gravitationa…
Low resolution spectroscopic investigation of Am stars using Automated method
Kaushal Sharma, Santosh Joshi, H. P. Singh
Automated method of full spectrum fitting gives reliable estimates of stellar atmospheric parameters (Teff, logg and [Fe/H]) for late A, F, G and early K type stars. Recently, the…
Estimating Stellar Atmospheric Parameters by Automated Methods Using SSLs
Kaushal Sharma, H. P. Singh, A. Kashyap +1
Libraries of stellar spectra, such as ELODIE (Prugniel & Soubiran 2001), CFLIB (Valdes et al. 2004), or MILES (Sánchez-Blázquez et al. 2006), are used for a variety of applications…