Szczegóły publikacji
Opis bibliograficzny
Real-time detection and classification of active regions from solar images using sector-based hashing / Rafał Grycuk, Rafał SCHERER, Giorgio De Magistris, Christian Napoli // Journal of Computational Science ; ISSN 1877-7503. — 2025 — vol. 89 art. no. 102604, s. 1–14. — Bibliogr. s. 14, Abstr. — Publikacja dostępna online od: 2025-05-22. — R. Scherer - dod. afiliacja: Czestochowa University of Technology
Autorzy (4)
- Grycuk Rafał
- AGHScherer Rafał
- De Magistris Giorgio
- Napoli Christian
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 162761 |
|---|---|
| Data dodania do BaDAP | 2025-09-22 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.jocs.2025.102604 |
| Rok publikacji | 2025 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Journal of Computational Science |
Abstract
We present a new approach for real-time retrieval and classification of solar images using a proposed sector-based image hashing technique. To this end, we generate intermediate hand-crafted features from automatically detected active regions in the form of layer-sector-based descriptors. Additionally, we employ a small fully-connected autoencoder to encode and finally obtain the concise Layer-Sector Solar Hash. By reducing the amount of data required to describe the Sun images, we achieve almost real-time retrieval speed of similar images to the query image. Since solar AIA images are not labeled, for the purposes of the presented test experiments, we consider images produced within a short time frame (typically up to several hours) to be similar. This approach has several potential applications, including searching, classifying, and retrieving solar flares, which are of critical importance for many aspects of life on Earth.
