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Simply stated, clustering involves gathering similar objects (data) into distinct clusters that are internally homogeneous and externally heterogeneous.
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The object data were divided into 160 blocks, and a separate hologram was prepared for each.
Image analysis involves the conversion of features and objects in image data into quantitative information about these measured features and attributes.
That is, each object beam is subdivided into two parts such as one inner part containing object data, called half-object beam, and the other outer part containing no object data, called half-reference beam.
The object-based approach involved segmentation of image data into objects at multiple scale levels.
Integrating Data into Objects Using Structural Knowledge.
They use them to organize "raw" data into objects, categories and events, and in doing so they infect even the most "reliable event data" with their partiality and subjectivity.
The process of converting byte-stream data into objects, known as 'unmarshalling', can take up to several minutes (~ 3 4 min for a 3 GB mzML file in an Intel® Core™ 2 Quad CPU at 2.83 GHz with 8 GB of RAM).
In this article, though, we follow the more direct route of encoding each type of data into objects called kernels and using a weighted combination of these in the final decision function, an approach called multiple kernel learning (MKL) (see Fig. 1).
The system built with the above concept provides the following abilities, 1) declarative description that engineers intend to design, 2) effective entering data into Object oriented model, 3 semantic of design model which focused by numerical simulation and graphics programed with Java.
Rich, T. "Encoding Data into Physical Objects with Digitally Fabricated Textures". Thesis.
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