Detection of astronomical objects in multi-band images

• Grant number: 24/19866-2
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: December 01, 2024
• End date: November 30, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Nina Sumiko Tomita Hirata
• Grantee: Tiago Gomes Dourado de Oliveira
• Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
• Associated research grant: 22/15304-4 - Learning context rich representations for computer vision, AP.TEM

Abstract

Optical telescopes capture images of large areas of the sky in multiple bands. From these signals, the aim is to recognize what each of the observed objects is. Initial approaches used measurements extracted by traditional image and signal processing methods to perform the classification. More modern approaches use neural networks and process the images directly. Due to the number of objects captured in these images, it becomes attractive to treat this problem as an object detection problem rather than an individual object classification problem. This project aims to investigate the use of the YOLO model in the recognition of multiple objects contained in astronomical images and contribute to a more efficient classification of objects in general.