Sentence examples for classification of targets from inspiring English sources
Defense and security surveillance scenarios typically involve the detection and classification of targets in complex and dynamic backgrounds.
However, because of the similar performance among top-ranked predictors over easy and difficult targets, the sequence identity based classification of targets does not seem to accurately reflect the uncertainty associated with a protein's true function (except for with BLAST).
We obtain mathematical and simulation models for the reflectivity of different homogeneous non-conducting materials and study the effect of such reflectivity on the classification of targets.
Because the number of pulses, time delay δ m, and the intensity α mn of the signal depends on the target shape and target element, we can use variation of the pulse width as a feature in classification of targets.
One key application is the detection and classification of targets on the ground under tree cover using airborne imagery, which is related to environmental mapping and is the focus of the Jigsaw [7] and Swedish Defence Research [8] systems.
This represents a first attempt to tackle the problem of detection and classification of targets behind walls with m-D signatures and much more work is expected to quantify performance.
Time-resolved multivariate classification of target type.
Time-resolved multivariate classification of target location.
(B) Average activation patterns31 supporting within-subject classification of target location from 200 350 ms post-onset, in Experiment 1 (Non-human faces, left) and Experiment 2 (Human faces, right) depending on target type (Exemplar target versus Category target).
(B) Average activation patterns31 supporting within-subject classification of target type from 100 250 ms post-onset, in Experiment 1 (Non-human faces, bottom) and Experiment 2 (Human faces, top) averaged over target locations.
Then, based on these nonlinear eigenspaces, the proposed method can perform the clustering of training HR patches in this subsection and the high-frequency component estimation, which simultaneously realizes the classification of target patches for realizing the adaptive reconstruction, in the following subsection.
