Arbitrary-Scale Downscaling of Tidal Current Data Using Implicit Continuous Representation

Numerical models have long been used to understand geoscientific phenomena, including tidal currents, crucial for renewable energy production and coastal engineering. However, their computational cost hinders generating data of varying resolutions. As an alternative, deep learning-based downscaling...

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Bibliografische Detailangaben

Hauptverfasser:	Dongheon Lee, Seungmyong Jeong, Youngmin Ro
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2024-01-01
Schriftenreihe:	IEEE Access
Schlagworte:	Arbitrary-scale downscaling image super-resolution implicit neural representation oceanic tidal current data
Online-Zugang:	https://ieeexplore.ieee.org/document/10714469/
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