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Semantic hashing for fast solar magnetogram retrieval

Grycuk Rafał, Scherer Rafał, Marchlewska Alina, Napoli Christian

Journal of Artificial Intelligence and Soft Computing Research

2022

Vol. 12, No. 4

299--306

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.

Analiza solarna budynków w celu zwiększenia efektywności energetycznej

Sobierajewicz P.

Przegląd Budowlany

2011

R. 82, nr 9

82-88