In this process, the segmentation task becomes a task of recognition of the given parts and the structuring task remains as it is.
This covers the segmentation of the application into tasks, the cooperation and communication between these tasks, the suitability of the processor cores for each of these tasks, etc.
In relation to this, Szafir et al. (2016) detailed four types of tasks (identification, summarization, segmentation, and structure estimation) that are well suited for ensemble displays because they utilize ensemble coding or the mental summarization of data.
Many of these computational tools utilize hidden Markov model (HMM) [ 9, 13, 19, 20, 22, 23, 26, 32, 33] because of its inherent capability of resolving segmentation tasks.
The IAM databases are easily the most widely used collections of handwritten samples employed for a variety of segmentation and recognition tasks.
In summary, we will design a patch for the VSD using contrast-enhanced cardiac CT images, in four tasks: A) segmentation of the heart and the great vessels, B) editing of the heart model in CAD software in order to expose the relevant anatomy, C) designing of a VSD patch and D) preparing the 3D printing of the heart model and the VSD patch.
The materials of word segmentation tasks are at least phrases, but we prefer naturally occurred sentences.
The database can be employed in a number of segmentation and recognition tasks at line, word or character levels.
Although the proposed model is designed with focus on the particular application at hand, it is general enough to be applied to a variety of different segmentation tasks.
In this research, we have divided the task to make a concept map into two sub-tasks: (1) "segmentation task" where parts of the concept map (nodes and links) are extracted from learning resources and (2) "structuring task" where the extracted parts are integrated into a map.
