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Classical direct volume rendering techniques accumulate color and opacity contributions using the standard volume rendering equation approximated by alpha blending. However, such standard rendering techniques, often also aiming at visual realism, are not always adequate for efficient data exploration, especially when large opaque areas are present in a data set, since such areas can occlude important...
The advent of highly accurate, large scale volumetric simulations has made data analysis and visualization techniques an integral part of the modern scientific process. To develop new insights from raw data, scientists need the ability to define features of interest in a flexible manner and to understand how changes in the feature definition impact the subsequent analysis of the data. Therefore, simply...
cDNA microarray expression data is widely used to help biomedical research. The data must be normalized because of various error functioned interferences existed. This paper has discussed the normalization for supervised multi-class (phenotype) data. All the classes are the type of multi-sample. Also, a reasonable hybrid cross-phenotype normalization (CPN) algorithm based on iterative nonlinear regression...
In this paper, we present a novel approach for automatically learning a compact and yet discriminative appearance-based human action model. A video sequence is represented by a bag of spatiotemporal features called video-words by quantizing the extracted 3D interest points (cuboids) from the videos. Our proposed approach is able to automatically discover the optimal number of video-word clusters by...
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