DNA sequence homology is a critical and fundamental problem in bioinformatics. In this paper, we solve this problem by use of the second order Markov modal instead of traditional sequence alignment because DNA charact...
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A vertex separator in an undirected graph is a subset of the vertices, whose removal disconnects the graph in at least two nonempty connected components. Given a connected undirected graph G = (V ,E) with |V| = n, an ...
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This paper introduces the theory of ϕ-Jensen variance. Our main motivation is to extend the connotation of the analysis of variance and facilitate its applications in probability, statistics and higher education. To t...
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Kernel independent component analysis (KICA) has been widely used in the field of blind source separation. The selection of kernel function and its parameters plays an important role in KICA algorithm performance. An ...
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ISBN:
(纸本)9781479979684
Kernel independent component analysis (KICA) has been widely used in the field of blind source separation. The selection of kernel function and its parameters plays an important role in KICA algorithm performance. An optimal kernel model should be rich enough to well map the given samples. However, users usually use a singular kernel based model in their experiments, which leads to a suboptimal kernel model. In order to solve this problem, we propose the evolution based multiple kernel independent component analysis (EMKICA), in which a convex combination of multiple base kernels is used instead of single kernel of KICA. The combination weights are learned by particle swarm optimization algorithm. Firstly, we elaborate the basic theory of KICA and concept of EMKICA, also the combination form of the composition kernel used in EMKICA. Secondly, we describe the presentation of the individuals in the particle swarm optimization algorithm, the settings of the evaluation function and general algorithm. Finally, we evaluate the separation ability of EMKICA on three different data sets including one-dimensional mixed signals, composite images and images with reflection. The experimental results verify the effectiveness of EMKICA.
A new method dealing with recognition of partially occluded and affine distortion objects is presented. The method is designed for objects with smooth curved boundary. It divides an object into affine-invariant parts ...
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A new method dealing with recognition of partially occluded and affine distortion objects is presented. The method is designed for objects with smooth curved boundary. It divides an object into affine-invariant parts based on the feature point. And a new approach for matching each part is presented in this paper. Robust Hausdorff distance (RHD) is introduced to measure the similarity between feature points set of model and that of target. In terms of the new RHD, the optimal affine transform can be estimated. And then the sub-curve match pairs are calculated based on the optimal affine transformation. The experimental results show proposed algorithm are capable of coping with partial occlusion and affine transformation.
In view of the draw backs of apple grade identification in China,which still relies on photoelectric sorting and manual separation,this paper presents a processing method on the basis of the technology of computer vis...
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In view of the draw backs of apple grade identification in China,which still relies on photoelectric sorting and manual separation,this paper presents a processing method on the basis of the technology of computer vision and digital *** image processing technology,the researcher calculated the length of the long-short-axis,marked the location of it and calculated the 4 parameters,color,mean square,shape,size,as the key characteristics of the BP input of network to build a network and identify the level of apple through analysis of the external characteristics of *** optimum structure parameters of the BP neural network which had 9 hidden layer neurons were determined by RP training *** showed that average accuracy for fruit classification can reach 92.5% by using this model,and the executing time of microcomputer for grading of one apple is 9.3 *** method has the characteristics of high accuracy and good real-time performance.
In view of the problem that the global optical flow algorithm cannot acquire accurate motion parameter estimation at a low-gradient value, an improved method has been presented in order to enhance the self-adaptive ab...
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Under the effect of solar variation, atmospheric attenuation and thermal radiation distribution, the grey value of interference source is close to or equal to the target grey value. With the distance between the imagi...
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One key challenge of facial trait recognition is the large non-rigid appearance variations due to some irrelevant real world factors, such as viewpoint and expression changes. In this paper, we explore how the shape i...
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ISBN:
(纸本)9781467369657
One key challenge of facial trait recognition is the large non-rigid appearance variations due to some irrelevant real world factors, such as viewpoint and expression changes. In this paper, we explore how the shape information, i.e. facial landmark positions, can be explicitly deployed into the popular Convolutional Neural Network (CNN) architecture to disentangle such irrelevant non-rigid appearance variations. First, instead of using fixed kernels, we propose a kernel adaptation method to dynamically determine the convolutional kernels according to the spatial distribution of facial landmarks, which helps learning more robust features. Second, motivated by the intuition that different local facial regions may demand different adaptation functions, we further propose a tree-structured convolutional architecture to hierarchically fuse multiple local adaptive CNN subnetworks. Comprehensive experiments on WebFace, Morph II and MultiPIE databases well validate the effectiveness of the proposed kernel adaptation method and tree-structured convolutional architecture for facial trait recognition tasks, including identity, age and gender recognition. For all the tasks, the proposed architecture consistently achieves the state-of-the-art performances.
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