Sentence examples for developing classification from inspiring English sources
She is focused on establishing a platform imaging modality that includes designing optical catheters and developing classification algorithms for real-time imaging of the heart.
These results show that both processors applied to copolarization and cross-polarization data might help developing classification rules.
Then, the extracted features were assessed by various multiclass least square support vector machine (MLS-SVM), classifying epileptic EEG signals; Aslan et al. [27] executed a study to check epileptic patients developing classification method.
When developing classification systems for familiar animals, the American students used morphology, behavior and size to inform their classification decisions whereas the Itzaj considered ecological factors, morphology and behavior (Lopez et al. 1997).
Then, for developing classification models, the developmental toxicity data set was divided in two classes, i.e. non developmental toxicant (N) and developmental toxicant (D), as indicated in Table 7. Class N merges the first two FDA categories A and B, and the class D includes all compounds belonging to categories C, D and X.
In this article a novel classification method, Decision Forest (DF), is proposed for developing classification models using omics data.
A previously developed classification system has identified different subgroups including active extension and multidirectional patterns in patients with CDLBP.
To describe and determine the intertester reliability of a newly developed classification system of shoulder syndrome recognition.
A near-infrared (NIR) hyperspectral imaging system was used to develop classification models to differentiate wheat classes grown in western Canada.
Two statistical techniques, i.e., linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used to develop classification models from the collected sensor signals.
"We developed classification methods for characterizing these locations from visual, textual and temporal features," said Daniel Huttenlocher, the John P. and Rilla Neafsey Professor of Computing , Information Scienceand Business and Stephen H. Weiss fellow.
