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A parallel algorithm should address the potential side effects introduced by task segmentation and guarantee a result that is identical to the original algorithm (serial version).
For a (large scale) matrix of size n=m2k (m,k⩾1) and p=2q (⩽n/2) available processors, we first construct an adequate 2-phases task segmentation and inducing a balanced layered task graph.
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The algorithm is divided into the following three tasks: segmentation, tracking, and size measurement.
The task of segmentation is to group nearby pixels into segments (objects) that may potentially represent leaves.
By introducing an image representation based on topological features, the task of segmentation is less dependent on variations of color or texture.
In this paper, we proposed a framework that used K-modes clustering technique as a preliminary task for segmentation of 11,574 road accidents on road network of Dehradun (India) between 2009 and 2014 (both included).
Among other tasks, object segmentation is perhaps the most important problem in single image processing.
In this process, the segmentation task becomes a task of recognition of the given parts and the structuring task remains as it is.
From this point of view, in the closed-end approach, the segmentation task is replaced with recognition task of parts and the structuring task remains as it is.
Participants performed two tasks, a semantic and a syllabic segmentation task, both of which involved action and non-action verbs.
Unlike in the Chinese word segmentation task, in the CHEMDNER task, category information of chemicals is associated with the tag set, leading to a high computational cost and training time.
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