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Aufsatz
Model selection, adaptation, and combination for transfer learning in wind and photovoltaic power forecasts
(2023-03-14)
There is recent interest in using model hubs – a collection of pre-trained models – in computer vision tasks. To employ a model hub, we first select a source model and then adapt the model for the target to compensate for differences. There still needs to be more research on model selection and adaption for renewable power forecasts. In particular, none of the related work examines different model selection and adaptation strategies for neural network architectures. Also, none of the current studies investigates the ...
Aufsatz
Experimental and numerical polarization analysis of the 3D transfer behavior in microsphere-assisted interferometry for 1D phase gratings
(2023-06-08)
Enhancing the lateral resolution in optical microscopy and interferometry is of great interest in recent research. In order to laterally resolve structures including feature dimensions below the Abbe resolution limit, microspheres in the optical near-field of the specimen are shown to locally improve the resolution of the imaging system. Experimental and simulated results following this approach are obtained by a high NA Linnik interferometer and analyzed in this contribution. They show the reconstructed surface of ...
Aufsatz
Optimised use of data fusion and memory-based learning with an Austrian soil library for predictions with infrared data
(2023-06-24)
Infrared spectroscopy in the visible to near-infrared (vis–NIR) and mid-infrared (MIR) regions is a well-established approach for the prediction of soil properties. Different data fusion and training approaches exist, and the optimal procedures are yet undefined and may depend on the heterogeneity present in the set and on the considered scale. The objectives were to test the usefulness of partial least squares regressions (PLSRs) for soil organic carbon (SOC), total carbon (Ct), total nitrogen (Nt) and pH using ...