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As shown, the output of TV lacks texture details.
As shown, the output of the classifiers corresponds to the input of the neural network.
Similar(58)
-axis shows the output value of the neural network.
Figure 10 shows the output image with retinal structures extraction.
Figure 6 shows the output of this stage.
Table 11 and Figure 9 show the output error.
Figure 6c shows the output brightness equalization without taking into account the retina output.
The top panel shows the output waveform for the onboard calibration.
Figure 8 shows the output the scheduler provided to the user.
Figure 9 shows the output power of MTs and PVs as well as the electrical load.
Figure 7 shows the output SINR performance of PA and MIMO radar in the abovementioned scenario.
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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