- Tytuł:
- Semantic hashing for fast solar magnetogram retrieval
- Autorzy:
-
Grycuk, Rafał
Scherer, Rafał
Marchlewska, Alina
Napoli, Christian - Powiązania:
- https://bibliotekanauki.pl/articles/2147145.pdf
- Data publikacji:
- 2022
- Wydawca:
- Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
- Tematy:
-
content-based image retrieval
image descriptor
solar analysis - Opis:
- We propose a method for content-based retrieving solar magnetograms. We use the SDO Helioseismic and Magnetic Imager output collected with SunPy PyTorch libraries. We create a mathematical representation of the magnetic field regions of the Sun in the form of a vector. Thanks to this solution we can compare short vectors instead of comparing full-disk images. In order to decrease the retrieval time, we used a fully-connected autoencoder, which reduced the 256-element descriptor to a 32-element semantic hash. The performed experiments and comparisons proved the efficiency of the proposed approach. Our approach has the highest precision value in comparison with other state-of-the-art methods. The presented method can be used not only for solar image retrieval but also for classification tasks.
- Źródło:
-
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 4; 299--306
2083-2567
2449-6499 - Pojawia się w:
- Journal of Artificial Intelligence and Soft Computing Research
- Dostawca treści:
- Biblioteka Nauki
Artykuł