Scholarship 22/11645-1 - Classificação de imagens, Aprendizagem profunda - BV FAPESP
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Classification of stars, galaxies, and quasars based on photometric multiband images

Grant number: 22/11645-1
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Start date until: October 01, 2022
End date until: November 30, 2024
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:Nina Sumiko Tomita Hirata
Grantee:Gabriel Jacob Perin
Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated research grant:15/22308-2 - Intermediate representations in Computational Science for knowledge discovery, AP.TEM
Associated scholarship(s):23/15047-4 - Model Merging for Large Language Model, BE.EP.IC

Abstract

The S-PLUS (Southern Photometric Local Universe Survey) project is collecting images of 12 bands of the southern hemisphere sky. In the context of this project, there is interest in the detection of quasars and other types of objects. In previous works, methods based on machine learning were developed to classify three types of objects (stars, galaxies, and quasars). One of the works used catalog data, including objects with missing data, while the other used images, without objects with missing data. The objective of this scientific initiation project is to compare these methods using a new data release, DR4, from S-PLUS. For this, the implementations of the methods will be reviewed and adapted to the new scenario and the evaluations will be carried out under experimental conditions directly comparable. The study will involve investigations into the treatment of missing data and pre-training of convolutional neural networks, to be used in image processing. Quantitative and qualitative comparisons of the two methods will be carried out to understand their differences.

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