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We present extensions to these works, which can considerably improve the efficiency of object delineation tasks.
The paper entitled "Object delineation by k-connected components" by Paulo Miranda et al. develops an image foresting transform for object delineation based on k-connected components with and without competition among seeds.
Heterogeneous stacking, an extension of stacked generalization for object delineation, improves pixel labeling and segmentation by training base classifiers on multiple target concepts extracted from the original ground truth, which are subsequently fused by the second set of classifiers.
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Accurate delineation of object borders is highly desirable in echocardiography, especially at the left ventricle.
In the case of both object and subject the delineation is constantly suspended; in other words, we never encounter full fixity.
The difficulty of accounting for the aesthetics involved in these activities from the participants' perspective is the same difficulty facing ambient aesthetics: the lack of clear delineation of object-hood of aesthetic experience.
To assess the efficacy and utility of our segmentation methods (in CT and PET images) quantitatively, we used accuracy measurements which are related to how well segmentation results compare with the true delineation of objects.
Establishing the true delineation of any object of interest (i.e., lung region, pathological object, etc).
Ground truths of delineation for the objects were obtained by expert radiologists' annotations.
This study proposes an object-based methodology, for detailed delineation and classification of soil types, using digital maps of topography and vegetation as soil covariates, based on Random forests classifier.
Little more than a quarter of the works in the show match a dictionary entry for "drawing" as "a graphic representation by lines of an object or idea, as by pencil; a delineation of form without reference to color".
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