Sentence examples for a hybrid classification from inspiring English sources

A hybrid classification procedure, which combined maximum-likelihood and decision-tree algorithms, was developed to classify the fraction images into land use and land cover classes.

Many readers on the other hand are interested, titillated even, in Mr. Chabon and Ms. Waldman, not just as writers, but as married-parent-writers, a hybrid classification that opens them up to commentary not just on their prose but also on their pairing and their parenting.

We used a hybrid classification technique, combining advantages from supervised and unsupervised methods, to derive a land cover map from three Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) images from 2000.

A hybrid classification method accurately discriminated urban and other land covers, despite the challenging desert environment, and landscape metrics were used to quantify the spatial evolution of the emirate.

For example, [31] demonstrate a multi-temporal and multi-sensor land-use change detection that involves a hybrid classification scheme.

Zhang et al. propose a hybrid classification technique (SVM-KNN) which selects features using k nearest neighbors [77] and classify using DAGSVM [78] classifier.

This paper presents a trifold hybrid classification (THC) approach for structural health diagnosis with unexampled health states (UHS), which comprises of preliminary UHS identification using a new thresholded Mahalanobis distance (TMD) classifier, UHS diagnostics using a two-class support vector machine (SVM) classifier, and exampled health states diagnostics using a multi-class SVM classifier.

The article entitled "Robust and Adaptive Diffusion-based Classification in Distributed Networks", by P. Binder, M. Muma, and A.M. Zoubir, describes a robust and adaptive distributed hybrid classification algorithm that is based on the diffusion principle.

We used a hybrid taxonomic classification algorithm, RITA [ 48], to provide an independent assessment of the phylogenetic affiliations of the assembled datasets.

We conduct a comprehensive performance evaluation which shows the proposed hybrid classification engine are able to detect six types of cardiac disorders with higher accuracy rate than the SVM-based classifier alone.

The distributed hybrid classification approaches are compared to a benchmark algorithm where the error rates are evaluated in dependence of different WSN parameters.