Sentence examples for average metric error from inspiring English sources

MOTP scores the average metric error when estimating multiple target 3D centroids, while MOTA evaluates the percentage of frames where targets have been missed, wrongly detected or mismatched.

Then, the Multiple Marker Tracking Accuracy (MMTA) is defined as the percentage of markers fulfilling the condition, and the Multiple Marker Tracking Precision (MMTP) as the average of the metric error between and, of all pairs fulfilling.

Facebook's VP of advertising apologized for the "average duration of video viewed" metric error, explaining that "The metric should have reflected the total time spent watching a video divided by the total number of people who played the video.

We refer to the final metrics in the two cases as optimized metric and average metric.

The performance assessment is carried out by means of the average bit error rate metric for some of the most widely used modulation formats on wireless optical links taking into account the atmospheric turbulence modeled either by the gamma-gamma or the negative exponential distribution model in conjunction with the pointing errors effect.

With the monotonicity of the distance in each sensor reading, we have suggested the average distance error as a metric in the functional quantization to construct the regular quantization partition such that the metric is iteratively reduced in the generalized Lloyd algorithm framework.

To construct regular quantization partitions, we suggest the average distance error as a metric in the functional quantization since the distance is monotonic in each sensor reading.

Specifically, we propose the average distance error as a metric since the functional quantization of the distance allows us to generate regular quantization partitions due to the monotonicity of the distance with respect to each sensor reading even when the nonlinear MMSE estimator for a source location is employed.

We extend our previous work by improving the overall algorithm with the use of a drift function to estimate learning parameters, that weighs the previous average quantization error and a new introduced metric: the average neuron utility.

The evaluation metric used for this part is the average prediction error.

In the first part of this paper, the performance analysis of dispersed spectrum cognitive radio systems is conducted in the context of communications applications, and average symbol error probability is used as the performance metric.