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In this paper, we propose a computational framework, called Image Re-Attentionizing, to endow the target region in an image with the ability of attracting human visual attention. In particular, the objective is to recolor the target patches by color transfer with naturalness and smoothness preserved yet visual attention augmented. We propose to approach this objective within the Markov Random Field...
In engineering applications, Gaussian process (GP) regression method is a new statistical optimization approach, to which more and more attention is paid. It does not need pre-assuming a specified model and just requires a small amount of initial training samples. Based on the design of experiment (DOE), determining a reasonable statistical sample space is an important part for training the GP surrogate...
In this paper, an adaptive optimization method based on Gaussian process (GP) surrogate model is proposed to minimize the warpage of injection molding parts. GP surrogate model combining design of experiment (DOE) methods is used to build an approximate function relationship between warpage and process parameters, replacing the expensive simulation analysis in the optimization iterations. First, establish...
A critical technology of automatic trajectory planning and control system for spray painting is segmenting complicated surfaces into multiple simple patches. This paper develops a new surface segmentation approach based on triangulated CAD model of part and deposition model of spray painting. First, the foremost segmentation generates the patches that are connected and can be covered by paths uniformly,...
Automatic sequence switching has been an important pursuit in the field of substation automation. This paper presents a software process simulation modeling representation and method for sequence switching strategy in substation. It starts with a presentation of sequence switching problem, then, suggests a component-driven pattern recognition model of a substation switch network organized in a logic...
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