By Arun C. Murthy, Vinod Kumar Vavilapalli, Doug Eadline, Joseph Niemiec, Jeff Markham
Read or Download Apache Hadoop YARN: Moving beyond MapReduce and Batch Processing with Apache Hadoop 2 (Addison-Wesley Data & Analytics Series) PDF
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A part of a chain of specialised publications on process Center—this publication offers a framework for making plans and providing a winning provider supervisor venture. Written through specialists at the Microsoft approach middle crew and with Microsoft MVP Mitch Tulloch as sequence editor, this name supplies concise tips, from-the-field insights, and most sensible practices for optimizing and conserving your carrier supervisor setting.
Post 12 months observe: First released December twenty second 2005
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Additional info for Apache Hadoop YARN: Moving beyond MapReduce and Batch Processing with Apache Hadoop 2 (Addison-Wesley Data & Analytics Series)
For example, based on a similar geodesic distance defined in , Criminisi et al.  computed the geodesic distance to offer a set of sensible and restricted possible segments, and obtained an optimal segmentation by finding the solution that minimizes the cost energy. Being different from the conventional global energy minimization, Criminisi et al.  addressed this problem by finding a local minimum. Another example is the geodesic graph-cut algorithm proposed by Price et al. . They used the geodesic distance to measure the regional term.
20. At each iteration, pixels in subregions adjacent to the foreground or background subregions are added to the active set. The initial seeds are then replaced by the centroids of generated homogeneous regions by involving added pixels. All pixels in the new subregion are assigned to the label of the seed point in the same subregion. 4 Region-Based Methods 49 Fig. 20 Two segmentation examples by using the SRG method . a A flower image with simple markups, where red for the foreground object and blue for background.
Being similar to Live-Wire, active contours use the edge features to derive an optimal object boundary under user guidance. All boundary points can be adjusted in parallel in an attempt to minimize the energy functional. This technique has been widely used in medical imaging when objects have similar shapes [45–47], where one can obtain prior knowledge of the desired contour conveniently. Kass et al.  introduced a global minimum energy contour. , the image gradient magnitude and the edge direction).