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Building on the mixed methods work synthesized here, systematic attention to indicator framing, selection, measurement, and analysis, could occur while maintaining flexibility and revisiting indicators as health RCS proceeds [ 46, 51].
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Here, the main idea of key frame selection is to select video frames which the camera locations with the route se are no larger than a predefined threshold r (e.g., 10 m).
Besides, we mainly used skip1 frame selection.
The experiments were done by using skip1 7-1-0 frame selection.
The frame selection for each iteration is randomized.
We used several frame selection numbers in the experiments.
Hereafter, we refer to Equation 8 as 'linear' frame selection and Equation 15 as 'skip1' frame selection.
Prediction architecture is described by the reference frame selection and reference frame ordering.
We can observe that the skip1 frame selection could almost always outperform the linear frame selection for the simulated noiseless reverberant data (Table2).
While for the simulated noisy reverberant data (Table3), the linear frame selection was better, although the skip1 frame selection could be better for some cases.
In Subsection 6.2, we did experiments using various frame selection types, frame selection numbers, and training data numbers on several simulated noiseless and noisy reverberant environments.
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