Sentence examples for addressed the classification from inspiring English sources

Exact(5)

This study addressed the classification of multi-temporal satellite data from RapidEye by considering different classifier algorithms and decision fusion.

Liwicki et al. [9] also addressed the classification of gender and handedness in the on-line mode (which means that the temporal information about the handwriting is available).

Even the three recent studies that have addressed the classification of ariids reveal considerable disagreement [ 15, 19, 21].

Piwowar and Chapman (2008b) also addressed the classification of articles (at the article level) for data sharing in five databases (GenBank, Protein DataBank, GEO, ArrayExpress, Stanford Microarray Database).

Demner-Fushman et al. (2005) addressed the classification of MEDLINE abstract sentences between seven clinical outcome categories in order to automatically identify outcome-related information in the medical text.

Similar(55)

In this paper, we introduces an alternative implementation technique for SVM to address the classification problem with small-size training sample set.

However, some papers partially address the classification of pansharpening methods, see [12] for instance, or relate already proposed techniques of more global paradigms [13 15].

– Bioinspired approaches In 'Data feature selection based on Artificial Bee Colony algorithm', Schiezaro and Pedrini present a bioinspired algorithm for feature selection to address the classification problem.

Specifically, we address the classification and feature measurement of multiple beach zones, a topic addressed to a lesser extent by other projects.

This paper presents a novel approach based on Helly property of Hypergraph and Arithmetic Residue-based Probabilistic Neural Network (HG AR-PNN) to address the classification problem in IDS.

Open data also helps address the classification problem, again by lowering the cost at which one group attempts to organize their information, and by creating a culture in which classification schemes are themselves shared, remixed, hacked, and subjected to incremental improvement-but also ready to be torn down and rebuilt when the data indicate.

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