Histogram is a type of bar chart that is used to represent statistical information by way of bars to display the frequency distribution of continuous data. It indicates the number of observations that lie in-between the range of values, which is known as class or bin. A histogram chart helps...
Histogram difference refers to a measure used in computer science to detect similarity between images by comparing changes in the weighted color histogram of the images. It is less sensitive to subtle motion and can be used to limit distortion caused by noise and motion in sub-regions of the ...
First a few basics. A histogram basically depicts an estimate of the probability distribution of some variable. To construct a histogram, the range of possible variable values gets divided into a series of intervals called bins. The bins must be adjacent to each other and are often (but necess...
In fact, SE is the standard deviation of the fitted parameter obtained from the nonlinear regression. There is no difference between SE and SD when we talk about fitted parameters in the curve fitting. Keywords:SE, SD, parameter, nonlinear curve fit, standard error, standard deviation...
Then, we built histograms of the height and surface of protein clusters and plot protein cluster height as a function of protein cluster surface. The histograms were normalized by the total number of clusters used for histogram building (Table 1). The histograms thus represent the probability of...
Owing to density difference, the brine permeated downward and passed through the underlying limestones, causing dolomitization (Adams and Rhodes, 1960; Machel, 2004; Lu and Cantrell, 2016) (Figure 8). For cycles 2–7 in the Xiaoerbulake Formation, the upper parts are primarily composed of ...
In this paper, a novel edge-based active contour method is proposed based on the difference of Gaussians (DoG) to segment intensity inhomogeneous images. DoG is known as a feature enhancement tool, which can enhance the edges of an image. However, in the
The red line is the kernel density estimate (KDE) curve for different numbers of calibration(CALI) from the ImageNet training set. whole training set. As described in Sec. 3.2, our regulariza- tion loss computes the distance between the quantized block activati...
Trees were segmented based on stem position and planting distance to gain points per tree (PPT) from each plant (Tsoulias et al., 2019). More specifically, the bivariate point density histogram enabled the detection of the peak of laser hits for each individual tree based in the assumption ...
'Path Length Difference' refers to the variance between the number of steps in the most parsimonious tree found for a specific data partition and the total number of steps in the combined analysis of all partitions. AI generated definition based on: Journal of Biomedical Informatics, 2006 About ...