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Figure 5 show experiments on multiple objects and inside holes segmentation.
We show experiments where a fused temperature forecast outperforms individual temperature forecasts from several providers.
We apply the ASDF hierarchy for preprocessing input images in a feature-based biologically motivated object recognition learning architecture and show experiments with this real-time vision system running at 6 Hz including the online learning of the segmentation.
We show experiments with two omnidirectional image data sets to evaluate the performance of the method and compare the results using the proposed radial lines with results from state-of-the-art wide-baseline matching techniques.
We illustrate our approach on a specific type of network robot system, called Peis-Ecology, and show experiments in which a sequence of configurations is automatically generated and executed on real robots.
For example, biology textbooks tend to show experiments with visualizations such as graphs.
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The figure shows experiments with different implementations of the filtering procedure.
For all conditions shown, experiments were performed in triplicate, on separate days and from separate transfections.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com