The phrase "alignment task" is correct and usable in written English.
It can be used in contexts related to ensuring that different elements or components are properly aligned or coordinated, often in technical or organizational settings.
Example: "The team is currently working on the alignment task to ensure that all departments are on the same page regarding project goals."
Alternatives: "synchronization task" or "coordination task".
In all these tests, CPU time is an important metric, as any alignment task is easy to perform by brute force if an aligner is given unlimited computer resources.
To demonstrate the alignment speed, the execution time required in performing one image alignment task is discussed.
Thus, for our image alignment task, we only compare the TNFN with the singleton-type NFN in the experimental section to prove that the TNFN outperforms the singleton-type NFN.
In this article, the steps of performing one image alignment task consists of capturing the template window from the input image, computing the feature within the window, and feeding the calculated feature into the trained network to get the affine parameters.
In this paper, we apply the proposed Bag-of-Iconic video representation for novel video analysis applications: in addition to the 3D model alignment task as in our earlier work [14], we demonstrate the usefulness of the Bag-of-Iconic video representation with a novel geometry-aware video retrieval task.
Homologous sites can be classified in any number of ways, and the genome alignment task usually targets the identification of certain classes of nucleotides.
The memory and resource requirements for the alignment tasks are computed using the formula provided by the SMALT aligner, and these values are passed to the appropriate job scheduler.
Such video clusters do not bring extra information for model alignment tasks.
In this article, DMELA is proposed for training a TNFN to perform image alignment tasks.
In this experiment, we utilize 240 testing images to perform image alignment tasks.
Although MGCSE is a good approach for training a TNFN, it would not be suitable for image alignment tasks.
