Szczegóły publikacji
Opis bibliograficzny
Enhancing solar magnetogram retrieval with deep semantic hashing and hierarchical graph indexing / Rafał Grycuk, Rafał SCHERER // W: ISD2025 [Dokument elektroniczny] : [33rd international conference on Information Systems Development] : September 3-5, 2025, Belgrade, Serbia] : empowering the interdisciplinary role of ISD in addressing contemporary issues in digital transformation: how data science and generative AI contributes to ISD? : proceedings / eds. I. Luković, [et al.]. — Wersja do Windows. — Dane tekstowe. — Gdańsk : University of Gdańsk ; Belgrade : University of Belgrade, 2025. — ( Proceedings of the International Conference on Information Systems Development ; ISSN 2938-5202 ). — e-ISBN: 978-83-972632-1-5. — S. [1–5]. — Wymagania systemowe: Adobe Reader. — Tryb dostępu: https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1721&con... [2025-12-04]. — Bibliogr. s. [5], Abstr. — R. Scherer - dod. afiliacje: Czestochowa University of Technology Faculty of Computer Science and Artificial Intelligence, Czestochowa, Poland ; Center of Excellence in Artificial Intelligence
Autorzy (2)
- Grycuk Rafał
- AGHScherer Rafał
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 164722 |
|---|---|
| Data dodania do BaDAP | 2025-12-15 |
| DOI | 10.62036/ISD.2025.45 |
| Rok publikacji | 2025 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Uniwersytet Gdański |
| Konferencja | International Conference on Information Systems Development 2025 |
| Czasopismo/seria | Proceedings of the International Conference on Information Systems Development |
Abstract
We present a method for content-based retrieval of solar magnetograms using semantic hashing. Based on HMI data from SDO and implemented with SunPy and PyTorch, the approach encodes magnetic regions as fixed-length vectors, avoiding full-disk image processing. A fully connected autoencoder compresses 400-dimensional descriptors into 50-dimensional semantic hashes. Experiments show that our method outperforms state-of-the-art techniques in precision and is also applicable to solar image classification.
