Sentence examples for investigated classification from inspiring English sources

Using synthetic images to simulate sub-pixel patch location, we investigated classification accuracy and extraction probability resulting from differences in the geometric properties of the raster grid and the feature alone.

In this work, we investigated classification performance of different methods and the corresponding fraction of ASD subjects who can be reliably classified as cases.

Five common evaluation criteria, including sensitivity, positive predictivity, accuracy, average accuracy, and t-test, are used to investigate classification performance.

The same sensor was used in [40] to investigate classification performance of a k-NN classifier as a function of what the authors named "clusters", for recognition of gender and for biometric.

A recent study from our institute investigating classification of DCIS by gene expression profiling confirms this finding and identified luminal, Her2-, and basal-like tumours in a series of 40 DCIS lesions (Hannemann et al, 2006).

To find the optimum number of mixtures for GMM classification and the optimum number of training iterations the influence of using one to eight mixtures was investigated for classification of four emotional speech styles and the influence of one to four mixtures was tested for recognition between male and female genders.

Character recognition is one of the most investigated pattern classification problems.

The Gaussian, Mexican Hat, and Morlet wavelet activation functions have been investigated for classification.

The multi-layer NMF networks was investigated for classification task by studying various network architectures and nonlinear functions.

In this section, performance of the proposed method is investigated considering classification accuracy obtained under different conditions, such as varying the feature dimension, utilizing different spectral bands for feature extraction and employing various types of kernel function in SVM classifier.

For all the methods investigated, the classification performance is affected by two key parameters: the patch size and the difference in quality factor between the first and second JPEG compressions, i.e., QF2 - QF1.