2 papers
astro-ph.IM2026
Classification of Astronomical Spectra Using PCA-Compressed Flux and Inverse-Variance Features
Bruno Santos Meneses Barreto, Marcio Eisencraft
This paper evaluates a signal-processing and supervised-learning pipeline for classifying SDSS DR17 astronomical spectra into stars, galaxies, and quasars. Each spectrum is represe…
astro-ph.IM2026
Multi-Variable Stellar Parameter Estimation Using Residual Multitask Neural Networks
Bruno Santos Meneses Barreto, Marcio Eisencraft
We present an end-to-end pipeline for estimating stellar parameters from Sloan Digital Sky Survey Data Release 12 spectra using a fully connected multitask neural network with resi…