3 papers
astro-ph.GA2026
Deep learning from the crowd Fundamentals of morphological galaxy classification
Luis Enrique Sucar, Carlos del Burgo, Jonathan Serrano-Pérez
Aims. The objective of this work is to adapt a deep neural network model to perform galaxy morphological classification trained from crowd annotations, considering the training sch…
astro-ph.IM2024
Bayesian and Convolutional Networks for Hierarchical Morphological Classification of Galaxies
Jonathan Serrano-Pérez, Raquel Díaz Hernández, L. Enrique Sucar
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,…
cs.LG2024
Semi-Supervised Hierarchical Multi-Label Classifier Based on Local Information
Jonathan Serrano-Pérez, L. Enrique Sucar
Scarcity of labeled data is a common problem in supervised classification, since hand-labeling can be time consuming, expensive or hard to label; on the other hand, large amounts o…