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Exact(17)
We used the same parameter values for all the test images.
In each round of simulations, both techniques used the same parameter values as described before.
Note that we have used the same parameter name S r for the parallel converted data at the input and the output of the Lorenz_Generator module because no change is made for this data at this module.
As regards convolutional filter size and pooling size, our findings on TIMIT indicated that the CNN is not particularly sensitive to the actual choice of these parameters, so we used the same parameter values that were found to be optimal for TIMIT.
We specifically used the same parameter values used in Figs.
We therefore used the same parameter settings for beamformer analysis as were employed in that study.
Similar(43)
We used the same parameters given in the previous section.
We used the same parameters when modelling the individual pathways and the negative and positive inter-pathway interactions.
All simulations used the same parameters unless otherwise noted.
Most studies used the same parameters; tidal volume and ventilation rate.
As discussed in [ 17], we used the same parameters for CNetA and CNetQ.
More suggestions(15)
used the same criterion
used the same metric
used the same variables
used the same end point
used the same criteria
used the same endpoints
uses the same parameter
used the same data
used the same metaphor
used the same number
used the -s parameter
used the same airport
used the same process
used the same line
used the same platform
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