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Support vector machine (SVM) is a method for the classification of both linear and nonlinear data.
We also develop a simple method for the classification of low-contrast images into either local or global low contrast.
In this paper, we propose a joint sparse coding based SPM (JScSPM) method for the classification of color medical images.
We present a general method for the classification of independent components (ICs) extracted from functional MRI (fMRI) data sets.
Although we have proposed a new method for the classification of cases and the accuracy is satisfactory, there are still many avenues for further research.
This paper proposes a new statistical test method for the classification of the two kinds of signals in consideration of the total error probabilities.
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This paper presents a refined taxonomy of instance selection and generation methods for the classification of data streams subject to concept drift.
It is found that the proposed filter bank outperforms other existing methods for the classification of seizure and seizure-free EEG signals.
In this context, the development of effective methods for the classification of forest types constitutes a crucial issue as forests represent the most widespread vegetation structure and play a key role in ecosystem functioning.
This work explores the use of characterization features extracted based on breast-mass contours obtained by automated segmentation methods, for the classification of masses in mammograms according to their diagnosis (benign or malignant).
A new harmonized EU regulation for the classification of waste came into effect on 1st June 2015, in which the criteria and assessment methods for the classification of hazardous waste are harmonized with other internationally agreed-upon systems for hazard classification of chemicals (CLP).
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