Sentence examples for performance of the features from inspiring English sources

The performance of the features will be tested on both clean video data and also video data corrupted in a variety of ways to assess each feature type's robustness to potential real-world conditions.

When evaluating the performance of the features on dataset-1 or dataset-2, the dataset is partitioned into the training sub-dataset and the validation sub-dataset in 50% versus 50% proportion to perform the cross-evaluation process.

Figure 8 shows the receiver operating characteristic (ROC) curves that compare verification performance of the features obtained from the Eigenfaces [13], scale-invariant feature transform (SIFT) [75], LBP [76], multiple kernel learning (MKL) [77], and the DGHMs.

We now test the performance of the features extracted using the techniques and parameters described in Section 4. First, 500 characters were randomly selected from the documents produced by each printer and copier in our dataset.

The present work investigates the performance of the features of Autoregressive (AR) parameters, which include gain and reflection coefficients, in addition to the traditional linear prediction coefficients (LPC), to recognize emotions from speech signals.

The classification performance of the features of AR parameters is studied using discriminant, k-nearest neighbor (KNN), Gaussian mixture model (GMM), back propagation artificial neural network (ANN) and support vector machine (SVM) classifiers and we find that the features of reflection coefficients recognize emotions better than the LPC.

"While Samsung will not collect your spoken word, Samsung may still collect associated texts and other usage data so that we can evaluate the performance of the feature and improve it," the policy states.

High values next to one are desired as they indicate a good performance of the feature.

For higher SNRs, this results in a decreasing performance of the feature.

Additionally, the smaller the relative absolute error is, the better the classification performance of the feature extraction algorithm is.

The performance of the feature manufacturing process affects the functional performance of the surface, and can be assessed by measurement of the resulting surface features.