Plan recognition,the inverse problem of plan synthesis,is important wherever a system is expected to produce a kind of cooperative or competitive *** plan recognizers,however,suffer the problem of acquisition and hand...
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Plan recognition,the inverse problem of plan synthesis,is important wherever a system is expected to produce a kind of cooperative or competitive *** plan recognizers,however,suffer the problem of acquisition and hand-coding a larger plan *** paper is aims to show that modern planning techniques can help build plan recognition systems without suffering such ***,we show that the planning graph,which is an important component of the classical planning system Graphplan,can be used as an implicit,dynamic planning library to represent actions,plans and *** also show that modern plan generating technology can be used to find valid plans in this *** this sense,this method can be regarded as a bridge that connects these two research *** and theoretical results also show that the method is efficient and scalable.
This paper proposed a novel hybrid probabilistic network,which is a good tradeoff between the model complexity and learnability in *** relaxes the conditional independence assumptions of Naive Bayes while still permit...
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This paper proposed a novel hybrid probabilistic network,which is a good tradeoff between the model complexity and learnability in *** relaxes the conditional independence assumptions of Naive Bayes while still permitting efficient inference and *** studies on a set of natural domains prove its clear advantages with respect to the generalization ability.
We augment Naive Bayes models by using divide and conquer strategy to address shortcomings of the standard Naive Bayes text classifier. The result is a generalized Bayes classifier which allows for local dependence am...
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We augment Naive Bayes models by using divide and conquer strategy to address shortcomings of the standard Naive Bayes text classifier. The result is a generalized Bayes classifier which allows for local dependence among feature subset;a model we refer to as the Augmented Naive Bayes (ANB) classifier. ANB relaxes the independence assumptions of Naive Bayes while still permitting efficient inference and learning. Experimental studies on a set of natural domains show that ANB has clear advantages with respect to the generalization ability.
Previous methods of volume rendering are very slow and thus impractical. We present volume rendering based on marching cubes iso-surfacing and transfer function. For an iso-surface, we divide the voxels into logical c...
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Previous methods of volume rendering are very slow and thus impractical. We present volume rendering based on marching cubes iso-surfacing and transfer function. For an iso-surface, we divide the voxels into logical cubes according to a predefined threshold value, the tangent planes and normal vectors at each voxel are calculated and the normal vectors are orientated to the outside of surface based on wide first searching (WFS), and the 3D surface model is then obtained using marching cubes. Transfer function is used to specify the optical properties for volume rendering technology. We employ a 2D function. The end-user interacts with a set of direct manipulation widgets (triangles and rectangles). Each widget precisely corresponds to a different material and widgets are blended automatically to compute an overall transfer function. Compared to traditional techniques, the overall specification process takes a fraction of the time.
This paper presents a new interest local regions descriptors method based on Hilbert-Huang Transform. The neighborhood of the interest local region is decomposed adaptively into oscillatory components called intrinsic...
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ISBN:
(纸本)1901725340
This paper presents a new interest local regions descriptors method based on Hilbert-Huang Transform. The neighborhood of the interest local region is decomposed adaptively into oscillatory components called intrinsic mode functions (IMFs). Then the Hilbert transform is applied to each component and get the phase and amplitude information. The proposed descriptors samples the phase angles information and amalgamates them into 10 overlap squares with 8-bin orientation histograms. The experiments show that the proposed descriptors are better than SIFT and other standard descriptors. Essentially, the Hilbert-Huang Transform based descriptors can belong to the class of phase-based descriptors. So it can provides a better way to overcome the illumination changes. Additionally, the Hilbert-Huang transform is a new tool for analyzing signals and the proposed descriptors is a new attempt to the Hilbert-Huang transform.
The necessary and sufficient condition for the existence of prewavelets with finite decomposition and finite reconstruction is presented. Especially when r = 1, we show that {φj(x-k) | 1 &le j &le r, k ∈ s} ...
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The necessary and sufficient condition for the existence of prewavelets with finite decomposition and finite reconstruction is presented. Especially when r = 1, we show that {φj(x-k) | 1 &le j &le r, k ∈ s} is shift-orthogonal if there exist prewavelets with finite decomposition and finite reconstruction, i.e., non-trivial prewavelets with finite decomposition and finite reconstruction does not exist. As an example, when r = 2 we construct a prewavelet with finite decomposition and finite reconstruction where the scale function is not shift-orthogonal, which demonstrate that there exist vector prewavelets with finite decomposition and finite reconstruction.
In this paper, we introduce two improvements on Ant Colony Optimization (ACO) algorithm: route optimization and individual variation. The first is an optimized implementation of ACO, by which the running time of ants ...
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In this paper, we put forward a fast simplification method for the terrain model by integrating the discrete particle swarm optimization with the hierarchical structure. In this method, each particle is represented as...
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It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotat...
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It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotation of new biological sequences is presented by using the variable-precision rough set theory. The proposed method is applied to the real data in GO database to examine its effectiveness. Numerical results show that the proposed method has better precision, recall-rate and harmonic mean value compared with existing methods.
This paper proposes a novel way for the population evolution research. In the paper, it constructs the phylogenies tree of four populations using the single nucleotide polymorphism (SNP) genotype frequency of human...
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