Based on the quotient space granular theorem, the image segmentation concept is analyzed and the image segmentation methods are studied, and then the quotient space granular theorem of image segmentation is demonstrat...
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Based on the quotient space granular theorem, the image segmentation concept is analyzed and the image segmentation methods are studied, and then the quotient space granular theorem of image segmentation is demonstrated. The image segmentation problems are described with triple elements function of the quotient space model (X,f,Γ)⇔([X],[f],[Γ]), according to the quotient space granularity computing, the image segmentation theorem is presented. The methods of images segmentation based on hierarchical and synthesis and combinational technique are exploited and then the segmentation algorithm based granularity synthesis technique is proposed. In this technique, the features of directionality and roughness in texture images data set are firstly extracted respectively to form the different granularities of image, then the different granularity are synthesized according to the theorem of granularity synthesis, finally the texture images is segmented. The experimental results demonstrate that the algorithm is valid for the segmentation of complicated texture images.
The future Web cart be imagined as a life network consisting of resource nodes and semantic relationship links between them. Any node has a life span from birth - adding it to the network - to death - removing it from...
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ISBN:
(纸本)158113844X
The future Web cart be imagined as a life network consisting of resource nodes and semantic relationship links between them. Any node has a life span from birth - adding it to the network - to death - removing it from the network. Through establishing and investigating two types of models for such a network, we obtain the same scale free distribution of semantic links. Simulations and comparisons validate the rationality of the proposed models.
An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for const...
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ISBN:
(纸本)158113844X
An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for constructing the semantic link network. The basic premise of this work is that the semantics of a web page can be reflected by a set of keywords, and the semantic relationship between two web pages can be determined by the semantic relationship between their keyword sets. The approach adopts the data mining algorithms to discover the semantic relationships between keyword sets, and then uses deductive and analogical reasoning to enrich the semantic relationships. The proposed algorithms have been implemented. Experiment shows that the approach is feasible.
Based on rank-1 update, Sparse Bayesian Learning Algorithm (SBLA) is proposed. SBLA has the advantages of low complexity and high sparseness, being very suitable for large scale problems. Experiments on synthetic and ...
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An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for const...
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ISBN:
(纸本)1581139128
An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for constructing the semantic link network. The basic premise of this work is that the semantics of a web page can be reflected by a set of keywords, and the semantic relationship between two web pages can be determined by the semantic relationship between their keyword sets. The approach adopts the data mining algorithms to discover the semantic relationships between keyword sets, and then uses deductive and analogical reasoning to enrich the semantic relationships. The proposed algorithms have been implemented. Experiment shows that the approach is feasible.
The future Web can be imagined as a life network consisting of resource nodes and semantic relationship links between them. Any node has a life span from birth -?adding it to the network -?to death -?removing it from ...
详细信息
ISBN:
(纸本)1581139128
The future Web can be imagined as a life network consisting of resource nodes and semantic relationship links between them. Any node has a life span from birth -?adding it to the network -?to death -?removing it from the network. Through establishing and investigating two types of models for such a network, we obtain the same scale free distribution of semantic links. Simulations and comparisons validate the rationality of the proposed models.
This paper concerns a greedy EM algorithm for t-mixture modeling, which is more robust than Gaussian mixture modeling when a typical points exist or the set of data has heavy tail. Local Kullback divergence is used to...
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This paper concerns a greedy EM algorithm for t-mixture modeling, which is more robust than Gaussian mixture modeling when a typical points exist or the set of data has heavy tail. Local Kullback divergence is used to determine how to insert new component. The greedy algorithm obviates the complicated initialization. The results are comparable to that of split-and-merge EM algorithm while the proposed algorithm is faster. Also the by product of a sequence of mixture models is useful for model selection. Experiments of synthetic data clustering and unsupervised color image segmentation are given.
Rough set theory is emerging as a new tool for dealing with fuzzy and uncertain data. In recent years, it has been successfully applied in such fields as machine learning, data mining, knowledge acquiring, etc. In thi...
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Stereo matching is one of the most active research areas in computer vision. In this paper, a fast stereo matching algorithm by means of epipolar constraint and multiresolution approach was presented. The searching sc...
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Stereo matching is one of the most active research areas in computer vision. In this paper, a fast stereo matching algorithm by means of epipolar constraint and multiresolution approach was presented. The searching scope of corresponding pixels in the original image is obtained and has diminished a lot based on multiresolution approach. Then intensity correlation principle and epipolar constraint can be applied to get the stereo matching results in this scope. In this way, we reduce the search time for correspondence and ensure the validity of matching. The experimental results show this algorithm is effective and efficient.
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