Sentence examples for small feature space from inspiring English sources

Unfortunately, such a small feature space makes distinguishing between many sequence classes challenging.

Therefore, in this study we propose a vehicle detection method that exploits the intrinsic structure of the vehicles in order to achieve good detection results while involving a small feature space (and hence low computational overhead).

For the (larger) ComParE set, the linear kernel SVMs are superior, while for the smaller EmoFt set, the RBF kernel appears to be the better choice, which is expected due to the initial small feature space dimensionality.

This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications.

Also note that a small vocabulary size or a low feature space dimension cannot account for the data.

For our application, it is sufficient to use a small Haar-like feature space, i.e. the first-order feature, which is the average value of a rectangular region; We used rectangles with a size of 20×20 pixels in the region of interest which is inside the tank (of size of 500×500); thus, L=625.

However, the distance from the center of major normal trajectories to this behavior class was relatively small in the trajectory feature space, causing many false detections.

The results obtained by them proved that the hierarchical Kohenen net in which each layer operates on a small subset of the feature space was superior to a Kohenen net operating on the entire feature space in detecting various kinds of attacks.

Elimination of the features of the weakest class discrimination ability (treated as the noise) leads to smaller dimension of the feature space and improvement of the generalization ability of the classifier in the testing mode for the data not taking part in learning.

To test this hypothesis, we evaluated the performance of the classifier when using only a small fraction of the original feature space.

In general, the precision of the algorithms used for feature extraction determine the smallest quantization steps of the feature space.