Temporally-consistent koopman autoencoders for forecasting dynamical systems
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-025-05222-7
Abstract: Absence of sufficiently high-quality data often poses a key challenge in data-driven modeling of high-dimensional spatio-temporal dynamical systems. Koopman Autoencoders (KAEs) harness the expressivity of deep neural networks (DNNs), the dimension reduction capabilities of autoencoders,… read more here.
Keywords: temporally consistent; dynamical systems; koopman autoencoders; consistent koopman ... See more keywords
Extracting Small Flying Airplane With Spatially Accurate and Temporally Consistent Foreground Modeling
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3121290
Abstract: Extracting the flying airplane from the satellite video has received a great deal of attention in remote sensing applications. Nevertheless, the challenge arises in two aspects: the limited spatial resolution of space-borne imaging devices and… read more here.
Keywords: temporally consistent; accurate temporally; flying airplane; spatially accurate ... See more keywords