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Št. zadetkov: 3
DIRECT 1.0
Grega Rovšček, Matjaž Ličer, Alexander Barth, Matej Kristan
Izvirni znanstveni članek
Oznake: rekonstrukcija geofizikalnih podatkov;difuzijski modeli;temperatura morske gladine;reconstruction of geophysical data;diffusion models;sea surface temperature;
Satellite sea surface temperature (SST) observations are frequently obscured by cloud cover, creating large gaps that must be reconstructed for many oceanographic and climate applications. Because multiple high-resolution SST fields may be consistent with the same sparse observations, this reconstru ...
Leto: 2026 Vir: Fakulteta za računalništvo in informatiko (UL FRI)
DINCAE 1.0
Alexander Barth, Aida Alvera-Azcárate, Matjaž Ličer, Jean-Marie Beckers
Izvirni znanstveni članek
Oznake: strojno učenje;konvolucijske nevronske mreže;interpolacija;površinska temperatura morja;satelitske meritve;
A method to reconstruct missing data in sea surface temperature data using a neural network is presented. Satellite observations working in the optical and infrared bands are affected by clouds, which obscure part of the ocean underneath. In this paper, a neural network with the structure of a convo ...
Leto: 2020 Vir: Nacionalni inštitut za biologijo (NIB)
CRITER 1.0
Matjaž Zupančič Muc, Vitjan Zavrtanik, Alexander Barth, Aida Alvera-Azcárate, Matjaž Ličer, Matej Kristan
Izvirni znanstveni članek
Oznake: globoko učenje;rekonstrukcijski algoritmi;satelitske meritve;deep learning;reconstruction algorithms;satellite measurements;
Satellite observations of sea surface temperature (SST) are essential for accurate weather forecasting and climate modeling. However, these data often suffer from incomplete coverage due to cloud obstruction and limited satellite swath width, which requires development of dense reconstruction algori ...
Leto: 2025 Vir: Nacionalni inštitut za biologijo (NIB)
Št. zadetkov: 3
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