GLCMGround-Launched Cruise Missile
GLCMGray Level Co-occurrence Matrix
GLCMGraduate of the London College of Music (UK)
GLCMGreat Lakes Crossing Mall (Auburn Hills, Michigan)
GLCMGerbil Lung Cell Conditioned Medium
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For example, the National Defense Authorization Act for Fiscal Year 2018 directs the development of a dual-capable GLCM with a maximum range between 500-5,500 km, in response to Russia's fielding a new GLCM that violates the Intermediate Nuclear Forces Treaty.
For global banking and markets (GB&M) business reported pre-tax profit was up 9% yoy for 2Q18 at USD2 billion, helped by business growth notably in GLCM and securities services, as well as in global banking lending, offset by lower revenue in the bank's rates and credit business due to tighter margins and more subdued client activity yoy.
Figure 1 shows the spatial sketch map of GLCM. If the remote sensing image has L picture gray levels, the size of the gray level co-occurrence matrix is L x L, d represents the distance of two pixels in the remote sensing image, [theta] represents the angle between the connection line of the two pixels and horizontal direction, and it is usually set as 0[degrees], 45[degrees], 90[degrees], and 135[degrees].
The low-level texture features, such as the mean of saturation in color space, contrast of GLCMs, and [L.sup.1] norm of wavelet coefficients extracted from vertical subband at level 1, have direct influence on high-level aesthetic feelings.
In our experiments, we use three types of aforementioned feature vectors including pixel intensity, standard deviations, and GLCM texture feature.
In this study, Gray-level Co-occurrence Matrix (GLCM) was used to represent texture [37].
Gray level cooccurrence matrix (GLCM) is a commonly used method for texture analysis, in which the texture features are extracted through statistical calculation.
Feature category Feature description Texture Haralick texture features [7] (1) Angular Second Moment (ASM), (2) Contrast, (3) correlation, (4) Sum of Squares of Variances (SSoV), (5) Inverse of Difference (IoD), (6) Sum of Average (SoA), (7) Sum of Variances (SoV), (8) Sum ofEntropy (SoE), (9) Entropy, (10) Difference of Variance (DoV), (11) Difference ofEntropy (DoE), (12) Gray-Level Concurrence Matrix (GLCM).
The main contribution of this study and the differences between our work and others mentioned previously lies on the application of the GLCM features for nonnegative matrix M and the use of a rank-two NMF instead of the hierarchical NMF.
GLCM is used for feature extraction and SVM is used for image classification.
Both GCLC and GLCM are controlled transcriptionally by a variety of cellular stimuli, including oxidative stress.