Based on the fusion of color and gradient features, this paper implements a novel approach to real-time background subtraction. Firstly, an energy function is defined based on the fusion of color and gradient features...
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Based on the fusion of color and gradient features, this paper implements a novel approach to real-time background subtraction. Firstly, an energy function is defined based on the fusion of color and gradient features. Secondly, the graph cuts based algorithm is employed to minimize energy function and segment the foreground. Finally, average optical flow is used to make inference about the validity of foreground regions, background models are then updated. The experimental results of different real scenes show that the proposed approach can produce real-time detection and promising results.
This paper proposes an edge detection scheme based on Fresnel diffraction mode. Since Fresnel diffraction is mathematically complex, it is simplified into a linear convolution filter. Experiments on images are compare...
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This paper proposes an edge detection scheme based on Fresnel diffraction mode. Since Fresnel diffraction is mathematically complex, it is simplified into a linear convolution filter. Experiments on images are compared with the Laplacian of Gaussian, Sobel and Canny edge detection algorithms. The experimental results indicate that the new detector's result is comparable to Canny detector and agree more with human's recognition. And it also can get an even better edge map on some regions which contain abundant local details or some tiny changes.
In this paper, a new image classification method is developed. This approach applies graph decomposition and probabilistic neural networks(PNN) to the task of supervised image classification. We use relational graphs ...
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Based on the clonal selection theory and immune memory theory, a novel artificial immune system algorithm, immune memory clonal programming algorithm (IMCPA), is put forward. Using the theorem of Markov chain, it is p...
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Based on the clonal selection theory and immune memory theory, a novel artificial immune system algorithm, immune memory clonal programming algorithm (IMCPA), is put forward. Using the theorem of Markov chain, it is proved that IMCPA is convergent. Compared with some other evolutionary programming algorithms (like Breeder genetic algorithm), IMCPA is shown to be an evolutionary strategy capable of solving complex machine learning tasks, like high-dimensional function optimization, which maintains the diversity of the population and avoids prematurity to some extent, and has a higher convergence speed.
Based on the chaos movement and the clonal selection theory, a novel artificial immune system algorithm, Adaptive Chaos Clonal Evolutionary Programming Algorithm （ACCEP）, is proposed in this paper. The new algorithm...
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Based on the chaos movement and the clonal selection theory, a novel artificial immune system algorithm, Adaptive Chaos Clonal Evolutionary Programming Algorithm （ACCEP）, is proposed in this paper. The new algorithm uses the Logistic Sequence to control the mutation scale and uses the Chaos Mutation Operator to control the clonal selection. Compared with SGA and Clonal Selection Algorithm, ACCEP can enhance the precision and stability, avoid prematurity to some extent, and have the high convergence speed. The results of the experiment indicate that ACCEP has the capability to solve complex machine learning tasks, like Multimodal Function Optimization.
In this paper, we propose a dimension reduction method of locality preserving projections based on QR-decomposition of training data matrix, namely LPP/QR. It is efficient and effective in under-sampled recognition of...
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The analytical study of a large scale nonlinear neural network is an uneasy *** try to analyze the function of neural systems by probing into the fuzzy logical framework of the neural ceUs'dynamical *** papers inv...
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ISBN:
(纸本)0780394224
The analytical study of a large scale nonlinear neural network is an uneasy *** try to analyze the function of neural systems by probing into the fuzzy logical framework of the neural ceUs'dynamical *** papers investigate the relation between fuzzy logic and neural *** most investigations focus on finding new function of neural system by combining fuzzy logical and neural system. In this paper,a novel approach is used to understand the nonlinear dynamic characteristics of neural system by analyzing the fuzzy logic framework of neural *** is the only way to understand the behavior of a large scale nonlinear neural *** abstracting the fuzzy logical framework of a neural cell,our analysis enables the delicate design of network *** an example,a difficulty task to build a recurrent network model of primary visual cortex by common dynamical analysis can be easily completed by this kind approach.
The theory of granule computing based on the quotient space is one of the three main granule computing theories. The emphasis is on the structure of the quotient space theory in this paper. Comparing with Rough Set th...
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Quotient space theory of problem solving, a formal model of granular computing, is generalized in the sense that topological structure is replaced by Cech's closure space. Some basic issues of granular computing, ...
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NKI contains a multi-domain oriented and large scale knowledge base. Text corpus is an important knowledge source of it. This paper presents an ontology-driven and integrated multi-agent architecture (MAKAT) for achie...
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