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ASP is based on active objects, asynchronous communications, and data-flow synchronizations.
We consider an object-oriented concurrency model for distributed systems, based on active objects, asynchronous method calls, and shared futures.
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In this article, object detection results based on Active Basis [4] are developed to replace supervised learning samples in object segmentation.
Novel forces in image segmentation based on active contours models are proposed for capturing objects in the image.
Tracking algorithms based on active contour will display the scheme of moving objects as a contour that will update in the consecutive frames dynamically.
Methods based on active contour according to the algorithm which is used to find object border will classify into the snakes and geodesic [25].
Our approach is based on active contours.
A light non-greasy formula based on actives extracted from Beech Tree Buds and stabilised using Ultra High Frequencies.
Such learning allows participants to predict the target object based on the preceding objects [14].
As shown in Figure 2, the algorithm first utilizes fragment connection and GraphCut segmentation to obtain the initial contour Ω 0 of the object based on the Active Basis model.
Separating clumped objects was carried based on shape of objects or maximum intensity values within a radius range depending on objects of interest.
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