A significant increase in the classification performance of a Bayesian classifier in crater detection using image texture features is observed.
Our findings suggest that the development and implementation of a multi-level system improves automation capabilities and increases accuracy in the classification of nerves.
Our experimental results indicate that the proposed network performs accurately and efficiently, achieving a reduction of the computation time and increasing the accuracy in the classification of hyperspectral images when compared to other traditional ANN techniques.
Among the five CpG methylation level groups, we observed a trend that when CpG methylation level increased, the proportion of CpG sites in that group increased as well (the classification of methylation level was described in the Materials and Methods section).
The use of two text-similarity-recognition programs also improved the rate of detection and, in some theses, significantly increased the classification of the gravity of the plagiarism encountered.
the simultaneous application of boosted LBP features, a bootstrapping procedure and sequential classification of race after the classification of gender lead to an increase in the accuracy of race classification by (sim )15% in comparison to the basic method.
However, the amount of the increase in the correct classification rate is relatively small.
The rapid expansion of seabed mapping studies has seen an increase in the application of automated classification techniques to efficiently map benthic habitats, and the need of techniques to assess confidence of model outputs.
While addition of the PO credits improved the sensitivity to detect de-escalation events classified by stewards, providing information on the route of antimicrobial administration to the experts in addition to the specific antimicrobials administered resulted in an increase in classification of de-escalation events in the vignettes.
If that assumption is generally true, then the 25-fold increase in the number of training patterns can improve classification accuracy by a substantial margin (conversely: if there is extensive between-subject variability in the patterns, then moving to a leave-one-subject out approach can hurt classification accuracy).
