Sentence examples for proportion of object from inspiring English sources

The relations between the minimal proportion of object within the computational window α min and the size of computational window T W can be defined as: {alpha}_{min }=frac{1}{T_W^2} (13).

To investigate the local property, HOS is estimated within an image using a sliding computational window, and α is denoted as the proportion of object within the computational window.

For the variance due to the limits of local statistics and the variation in the proportion of object-dependent information, Sánchezet al. [35] proposed to augment the descriptors with their spatial locations and create a bounding box for the local features.

For example, the vast majority of 3020-size samatch matoh to within 3%—irrespective of the population size (provided of course that it is larger than 3020) and the proportion of objects with the characteristic under investigation.. Maher also objects that the attribute itself, such as "blue", might be a priori relevant to its proportion in the sample and hence to matching.

If you draw a unit square on a piece of paper and inscribe a circle in it, and then randomly drop a collection of objects inside the square, the proportion of objects that land in the circle would be roughly equal to π/4.

With such a protocol, performance at the basic level of categorization can be compared on the same sets of dog-target images whereas the set of non-targets differs in its composition by the proportion of objects belonging to the same superordinate category.

In object-detection tasks, this would correspond to the proportion of objects in the image set detected by the method, and the proportion of non-object locations classified as objects.

In the database, sets of items can be characterised by its support (noted as supp), which is the proportion of objects sharing the attributes [ 13, 14].

The coarse-scale model is evolved to optimise the detection rate, i.e., the proportion of objects present in the training set that are detected by the ensemble of runs of act-detect.

The rules are characterized by various parameters, such as examples (i.e., number of objects covering a given rule), strength (i.e., the proportion of objects covered by premise that are also covered by conclusion), or confirmation (i.e., measure that is quantifying the degree to which premise provides evidence for conclusion).

The p value for the comparison of a dog's object selection against chance in a particular condition was determined as the proportion of simulated object selections in which the number of correct object selection was as high as or higher than that of dog's actual object selection.