Sentence examples for methods operate on from inspiring English sources
Region-level methods operate on a set of pixels and commonly rely on textural information for shadow detection [29, 30].
In this case, the methods operate on more local constraints trying to ensure, for example, that there are no abrupt changes in the timbre of two adjacent segments.
These methods operate on a population of potential solutions, applying the principle of survival of the fittest to produce better and better approximations to a solution, just as in natural adaptation.
On the other hand, these methods operate on the assumption that all low energy conformations can be created by combinations of low-energy fragments an assumption that is not always fulfilled.
Because T is calculated from row vectors, it can be demonstrated that KNN operating on T may capture information complementary to that of the respective PLS models (virtually all multivariate methods operate on column vectors).
Since both methods operate on possible sequences represented by paths through the tree, we adopt the complexity of computing the metric for a length-n path as the comparison criterion.
More recently, some researchers advocated for the computation of optimal weights on individual networks for a group of labels, and achieved better performance than the methods operating on single labels.
In this work, we define the input views that a DIBR method operates on as original views and output views it produces as the virtual (i.e. rendered) views.
Because activity measured by this method operates on a specific feature of the environment and yields a programmed consequence, we refer to it as operant activity.
We show that this framework forms the basis of a unified approach to analyze asynchronous implementations of stochastic optimization algorithms.In this framework, asynchronous stochastic optimization algorithms can be thought of as serial methods operating on noisy inputs.
Different from local methods operating on local regions of images, the non-local methods utilize non-local information (even the whole image) to accomplish image denoising.
