检索结果-南通市图书馆

Image retrieval based on color features integrated with anisotropic directionality

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2010年第1期21卷 127-133页

作者： Jing Bai Xiaohua Wang licheng jiao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 P. R. China

A novel image retrieval approach based on color features and anisotropic directional information is proposed for content based image retrieval systems （CBIR）. The color feature is described by the color histogram （CH）, which is translation and rotation invariant. However, the CH does not contain spatial information which is very important for the image retrieval. To overcome this shortcoming, the subband energy of the lifting directionlet transform （L-DT） is proposed to describe the directional information, in which L-DT is characterized by multi-direction and anisotropic basis functions compared with the wavelet transform. A global similarity measure is designed to implement the fusion of both color feature and anisotropic directionality for the retrieval process. The retrieval experiments using a set of COREL images demonstrate that the higher query precision and better visual effect can be achieved.

关键词： image retrieval color histogram directionlet transform anisotropic similarity.

Support vector classifier based on principal component analysis

在线全文

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2008年第1期19卷 184-190页

作者： Zheng Chunhong jiao licheng Li Yongzhao School of Electronic Engineering Xidian Univ. Xi'an 710071 P. R. China

Support vector classifier （SVC） has the superior advantages for small sample learning problems with high dimensions, with especially better generalization ability. However there is some redundancy among the high dimensions of the original samples and the main features of the samples may be picked up first to improve the performance of SVC. A principal component analysis （PCA） is employed to reduce the feature dimensions of the original samples and the pre-selected main features efficiently, and an SVC is constructed in the selected feature space to improve the learning speed and identification rate of SVC. Furthermore, a heuristic genetic algorithm-based automatic model selection is proposed to determine the hyperparameters of SVC to evaluate the performance of the learning machines. Experiments performed on the Heart and Adult benchmark data sets demonstrate that the proposed PCA-based SVC not only reduces the test time drastically, but also improves the identify rates effectively.

关键词： support vector classifier principal component analysis feature selection genetic algorithms

SAR Image Despeckling Using Scale Mixtures of Gaussians in the Nonsubsampled Contourlet Domain

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2015年第1期24卷 205-211页

作者： CHANG Xia jiao licheng LIU Fang SHA Yuheng Institute of Image Processing and Understanding School of Mathematics and Information Science Beifang University of Nationalities Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China International Research Center for Intelligent Perception and Computation Xidian University School of Computer Science and Technology Xidian University

The edge and contour details in SAR images are important for subsequent processing tasks. The multiscale geometric analysis method — Nonsubsampled contourlet transform(NSCT) is able to capture the geometric information of SAR images effectively. Describing the aggregation behavior of the neighborhoods coefficients, the scale mixtures of Gaussians model has exhibited favorable performances. A novel SAR image despeckling method is presented by constructing the scale mixtures of Gaussians model of NSCT. This method models the SAR images using the multiscale and multidirection information in NSCT domain. The dependency relationship of NSCT neighborhoods coefficients are also taken into consideration in our model. The speckle noise coefficients are shrinkaged by statistical prior estimation based on SAR image model constructed. Experimental results demonstrate that our method is advantageous at directional information preservation and the speckle restraint.

关键词： Synthetic aperture radar(SAR) image despeckling Stationary wavelet transform Nonsubsampled contourlet transform Scale mixtures of Gaussians model.

Distributed Parameter Neural Networks via Adaptive Wavelet

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 1993年第2期4卷 48-62页

作者： Zhuoer, Shi licheng, jiao Zheng, Bao Xidian Univ Xi'an China

The paper outlines a new neural net (DPNN) for describing brain's action based on one-dimensional cable theory. While the traditional neural network system only finding its character involving time changing (as HNN, BP etc.), the model-DPNNs (Distributed parameter neural networks) are not only the transmitted neurons of time variation, but also the functions of positions by the voltage u(x,t). With the neuroscientific relevance, some bioneural features like intermittent conduction and dendritic spike are fixed well by DPNNs which considered as complicated and adaptive devices contract to the functional elementary units. To find the semi-analytical representations of DPNNs, adaptive wavelets are utilized as new microlocalization tools. While maintaining all advantages of wavelet function, the adaptive wavelet offers a viable alternative learning procedure to the orthogonal least squares method (OLS), adaptive wavelet method develops a fairly general low-cost multiscale method for neural net optimization. In addition, a Lyapunov function method is also used to study the uniform asymptotic stability of DPNNs to support the new theory.

关键词： Brain Neurology Optimization

Optimal approximation of linear systems by artificial immune response

在线全文

学校读者我要写书评

暂无评论

Science in China(Series F) 2006年第1期49卷 63-79页

作者： GONG Maoguo DU Haifeng jiao licheng Institute of Intelligent Information Processing and Key Laboratory of Radar Signal Processing Xidian University Xi'an 710071 China School of Mechanical Engineering Xi'an Jiaotong University Xi'an 710049 China

This paper puts forward a novel artificial immune response algorithm for optimal approximation of linear systems. A quaternion model of artificial immune response is proposed for engineering computing. The model abstracts four elements, namely, antigen, antibody, reaction rules among antibodies, and driving algorithm describing how the rules are applied to antibodies, to simulate the process of immune response. Some reaction rules including clonal selection rules, immunological memory rules and immune regulation rules are introduced. Using the theorem of Markov chain, it is proofed that the new model is convergent. The experimental study on the optimal approximation of a stable linear system and an unstable one show that the approximate models searched by the new model have better performance indices than those obtained by some existing algorithms including the differential evolution algorithm and the multi-agent genetic algorithm.

关键词： approximation of linear systems artificial immune systems immune response clonal selection,immunological memory

Reference direction based immune clone algorithm for many-objective optimization

在线全文

学校读者我要写书评

暂无评论

Frontiers of Computer Science 2014年第4期8卷 642-655页

作者： Ruochen LIU Chenlin MA Fei HE Wenping MA licheng jiao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education International Research Center for Intelligent Perception and Computation Xidian University Xi'an 710071 China

In this paper, a new preference multi-objective optimization algorithm called immune clone algorithm based on reference direction method （RD-ICA） is proposed for solving many-objective optimization problems. First, an intelligent recombination operator, which performs well on the functions comprising many parameters, is introduced into an immune clone algorithm so as to explore the potentially excellent gene segments of all individuals in the antibody pop- ulation. Second, a reference direction method, a very strict ranking based on the desire of decision makers （DMs）, is used to guide selection and clone of the active population. Then a light beam search （LBS） is borrowed to pick out a small set of individuals filling the external population. The proposed method has been extensively compared with other recently proposed evolutionary multi-objective optimization （EMO） approaches over DTLZ problems with from 4 to 100 objectives. Experimental results indicate RD-ICA can achieve competitive results.

关键词： many-objective optimization preference multiobjective optimization artificial immune system reference direction method light beam search intelligent recombination operator

FWNN for Interval Estimation with Interval Learning Algorithm

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 1998年第1期9卷 56-66页

作者： Wang, Ling Liu, Fang jiao, licheng State Key Lab of RSP and NN Research Center Xidian University Xi'an 710071 P. R. China

In this paper, a wavelet based fuzzy neural network for interval estimation of processed data with its interval learning algorithm is proposed. It is also proved to be an efficient approach to calculate the wavelet c... 详细信息

关键词： Fuzzy wavelet neural network (FWNN) Interval learning algorithm.

高校科研实验室文化建设在创新人才培养中的探索与实践——以智能感知与图像理解教育部重点实验室为例

在线全文

学校读者我要写书评

暂无评论

西安电子科技大学学报（社会科学版） 2024年第2期34卷 103-107页

作者：张丹王鑫侯彪焦李成西安电子科技大学人工智能学院陕西西安710071 智能感知与图像理解教育部重点实验室陕西西安710071

高校科研实验室是科技创新和人才培养的重要载体,是“双一流”建设的重要支撑。实验室文化建设是实验室的精神内涵,该工作以学生为核心,从提升科学素养、激发探索欲望、培养创新精神、增强实践能力四个方面逐层展开,是建设优质育人环境... 详细信息

高校科研实验室是科技创新和人才培养的重要载体,是“双一流”建设的重要支撑。实验室文化建设是实验室的精神内涵,该工作以学生为核心,从提升科学素养、激发探索欲望、培养创新精神、增强实践能力四个方面逐层展开,是建设优质育人环境不可分割的重要组成部分。本文针对“培养什么人”这一基本问题提出了“如何培养创新人才”,从精神引领、制度建设和创新领航三个方面进行了探讨,同时分享了智能感知与图像理解教育部重点实验室在文化建设方面的探索与实践,以期为实验室文化建设提供参考和借鉴。

关键词：实验室文化建设创新人才培养精神引领制度建设创新领航

维普期刊数据库博看期刊

Image segmentation based on differential immune clone clustering algorithm

在线全文

学校读者我要写书评

暂无评论

International Journal of Intelligent Computing and Cybernetics 2013年第1期6卷 83-102页

作者： Wenping Ma Feifei Ti Congling Li licheng jiao Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China Xidian UniversityXi’anChina

Purpose–The purpose of this paper is to present a Differential Immune Clone Clustering Algorithm(DICCA)to solve image ***/methodology/approach–DICCA combines immune clone selection and differential evolution,and two populations are used in the evolutionary *** reproduction and selection,differential mutation,crossover and selection are adopted to evolve two populations,which can increase population diversity and avoid local *** extracting the texture features of an image and encoding them with real numbers,DICCA is used to partition these features,and the final segmentation result is ***–This approach is applied to segment all sorts of images into homogeneous regions,including artificial synthetic texture images,natural images and remote sensing images,and the experimental results show the effectiveness of the proposed ***/value–The method presented in this paper represents a new approach to solving clustering *** novel method applies the idea two populations are used in the evolutionary *** proposed clustering algorithm is shown to be effective in solving image segmentation.

关键词： Differential evolution Clone selection Clustering Image segmentation Image processing Cluster analysis