Regression analysis of fibre density (FD) and texture (square root transformation)
Muscle fibre density in relation to the colour and texture of smoked Atlantic salmon (Salmo salar L.)
... and texture characteristics In order to investigate the relationship between the textural characteristics of the smoked fillet and the fibre density of the raw starting material, the data for the two ...
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Original Article Logistic regression analysis of texture features of thyroid calcification based on computed tomography images
... the texture of calcification. Texture analysis refers to the process of extracting tex- ture feature parameters through certain image processing technology so as to obtain quantita- tive or ...
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TEXTURE ANALYSIS BY USING LINEAR REGRESSION MODEL BASED ON WAVELET TRANSFORM
... linear regression analysis, the distribution of the random data approximately appears a straight line in X, Y space when X and Y are perfectly related ...linear regression equation) can be given as ...
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A. Fibre density and moisture content
... D. Thermogravimetric analysis (TGA) The decomposition temperature of treated and untreated oil palm fibres was examined with TGA technique. The fibres were weighted of 10 mg and tested under argon atmosphere. ...
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Ranking of fibre-reinforced composite plate surface finish quality by wavelet texture analysis
... characteristic analysis length at level six that make the major contribution to the PC1 score for the ...the analysis level. Hence, at analysis level six, the characteristic length is approximately ...
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The XPS Analysis of Surface Texture of Different-Density-Level Coking Coal of Fenxi County
... element analysis arising in recent years, with a possession of a high recognition capacity of chemical characteristics of material surface and no damage of sample textures [1] ...quantitative analysis and ...
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Regression Based Crowd Density Estimation
... I. INTRODUCTION Recent work on crowd counting using low-level feature regression has shown promise in computer vision. One advantage with these methods is that they bypass intermediate processing stages, such as ...
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Nonparametric circular methods for density and regression
... statistical analysis (descriptive statistics, circular models, tests), graphical representation and some circular datasets; CircNNTSR package (Fern´ andez-Dur´ an and Gregorio-Dom´ınguez, 2012) which implements ...
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Analysis of thermal and mechanical properties of low density polyethylene (LDPE) with glass fibre (GF) Composites
... SHORT FIBRE REINFORCED POLYMER COMPOSITES In short-fibre reinforced polymers, loads are not directly applied to the fibre ...the fibre through the fibre ends; to be precise through the ...
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Beyond breast density: a review on the advancing role of parenchymal texture analysis in breast cancer risk assessment
... frequency of neighboring intensity values. Run-length fea- tures capture the coarseness of texture in specified di- rections by measuring strings of consecutive pixels (i.e., runs) which have the same gray-level ...
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Bayesian density regression and predictor-dependent clustering
... In fact, the model in (4.1) provides a flexible modeling framework, so that it can be used under two different analytic purposes: confirmatory and exploratory analysis. The model specification that we have ...
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A convolution estimator for the density of nonlinear regression observations
... The squared bias is smallest in almost all cases for the convolution estimator. This comes as a somewhat unexpected bonus of our method, since from the asymptotic analysis the bias is of the same order as for the ...
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Density Regression Based on Proportional Hazards Family
... Numerical Analysis In this section we first carry out some numerical analysis to illustrate the performance of the proposed Gt-PH regression method and make some comparison with MLE-based inference, ...
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Classification of ordered texture images using regression modelling and granulometric features
... investigated texture analysis and classification techniques to develop a more automated ...component analysis (PCA) and the self-organising map (SOM) clustering technique, however these were unable ...
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Detection of High-Density Crowds in Aerial Images Using Texture Classification
... employ regression-based methods for crowd counting and crowd density ...or regression–based approaches would fail. We compare two texture–classification methodologies on a dataset of aerial ...
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Micro-fibre based Porous Composite Propellants with High Regression Rates
... 2017, DESIDOC 1. IntroductIon Energy sources which are efficient, compact and safe to handle are always desired. Rapid gas generation using these energy sources for generating thrust or to perform some work, by adopting ...
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Density in a censored regression model.
... Thus, Q in this case is the best approximation to f by a density satisfying the constraints in H.. The next section gives conditions under which e,h are identifiable and the expected log[r] ...
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Deep learning for texture and dynamic texture analysis
... the analysis of textures and DTs using convolutional net- works and deep ...learning. Texture and DT analysis is crucial in various applications including remote sensing, industrial inspection, ...
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Predictive Density Estimation for Multiple Regression
... Abstract Suppose we observe X ∼ N m (Aβ, σ 2 I) and would like to estimate the predictive density p(y | β) of a future Y ∼ N n (Bβ, σ 2 I). Evaluating predictive estimates ˆ p(y | x) by Kullback- Leibler loss, we ...
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Nonparametric Mixed-Effects Density Regression
... kernel density esti- mation methods for dependent ...kernel density estimation methods for clustered ...dynamic density estima- tion for time-varying ...population density, and a hierar- ...
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