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SimRank is an effective structural similarity measurement between two vertices in a graph, which can be used in many applications like recommender systems. Although progresses have been achieved, existing methods still face challenges to handle large graphs. Besides huge index construction and maintenance cost, the existing methods require considerable search space and time overheads in the online...
Semantic issues are highly concerned with high-level interpretation in image understanding, which include text-image gap and its own affinity. Concentrating on text-formatting with entities in images, three sophisticated methodologies are roundly reviewed as generative, discriminative and descriptive grammar on the basis of contextual features. The following objective benchmark for visual words is...
Conventional contour tracking algorithms with level set often use generative models to construct the energy function. For tracking through cluttered and noisy background, however, a generative model may not be discriminative enough. In this paper we integrate the discriminative methods into a level set framework when constructing the level set energy function. We train a set of weak classifiers to...
Computational structure prediction, including de novo and homology modeling, is an important tool for membrane protein studies. Developing an accurate scoring function that can be used for structure discrimination and assessment remains a challenge. In our previous work, we have analyzed a set of high-resolution membrane protein structures using the network approach developed in our lab and proposed...
Flat Graph Model has become a very active direction in Image Understanding (IU) field, which constructs the probabilistic model of analysis object, processes parameter learning and probability inference, and obtains the final recognition result by analyzing maximum a posteriori. Image Under-standing could be regarded as labeling each pixel or patch independently. Flat graph model, latent generative...
In the recognition of ambiguous and multivocal model, the perception of the human will oscillate. In this paper, the synergetic pattern recognition theory is utilized to study the perception of the ambiguous and multivocal model. The biology significance of attention parameters and dynamic property of order parameters are researched. The generant condition in which the perception of ambiguous model...
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