检索结果-内蒙古大学图书馆

2011 6th International Conference on Pervasive computing and Applications, ICPCA 2011

作者： Zongmin, Li Yang, Liu Hua, Li School of Computer and Communication Engineering China University 0f Petroleum Shandong 257061 China Key Laboratory Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing l0080 China

ISBN: (纸本)9781457702082

Relevance feedback based on SVM classifier shows a good performance recently but the finite feedback counts limited by user's patience and the small sample size problem are not solved well, Co-SVM does a good job in solving these problems but still has some flaws. We propose three strategies to try to improve this algorithm: (1) different kernel functions are used to characterize the color and texture visual similarities;(2) a new method is proposed to caculate the confident scores of the contention samples;(3) a bunch of the most irrelevant images with the highest confident score are added into the labeled images to extend the size of labeled data while choosing a bunch of images for user labeling. Experimental results verify the superiority of our method over Co-SVM. © 2011 IEEE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Robust and discriminative image authentication based on sparse coding

Robust and discriminative image authentication based on spar...

引用

2011 IEEE Consumer Communications and Networking Conference, CCNC'2011

作者： Mou, Luntian Huang, Tiejun Tian, Yonghong Lian, Shiguo Chen, Xilin Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China Graduate University of Chinese Academy of Sciences Beijing China Institute of Digital Media Peking University Beijing China France Telecom RandD Beijing China

ISBN: (纸本)9781424487905

Image authentication is usually approached by checking the preservation of some invariant features, which are expected to be both robust and discriminative so that content-preserving operations are accepted while content-altering manipulations are rejected. However, most of existing features have not obtained convincing performance due to insufficiency of experiments and over biasing of robustness. Motivated by the sparse coding strategy discovered in primary visual cortex, we explore the possibility of using sparse coding coefficients for image authentication. Through extensive experiments, we discover that the proposed feature bears great discrimination as well as robustness, which indicates the effectiveness of sparse coding as a new invariant feature for image authentication. © 2011 IEEE.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Visual saliency detection by spatially weighted dissimilarity

Visual saliency detection by spatially weighted dissimilarit...

引用

作者： Duan, Lijuan Wu, Chunpeng Miao, Jun Qing, Laiyun Fu, Yu College of Computer Science and Technology Beijing University of Technology Beijing 100124 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Information Science and Engineering Graduate University Chinese Academy of Sciences Beijing 100049 China Department of Computing University of Surrey Guildford Surrey GU2 7XH United Kingdom

ISBN: (纸本)9781457703942

In this paper, a new visual saliency detection method is proposed based on the spatially weighted dissimilarity. We measured the saliency by integrating three elements as follows: the dissimilarities between image patches, which were evaluated in the reduced dimensional space, the spatial distance between image patches and the central bias. The dissimilarities were inversely weighted based on the corresponding spatial distance. A weighting mechanism, indicating a bias for human fixations to the center of the image, was employed. The principal component analysis (PCA) was the dimension reducing method used in our system. We extracted the principal components (PCs) by sampling the patches from the current image. Our method was compared with four saliency detection approaches using three image datasets. Experimental results show that our method outperforms current state-of-the-art methods on predicting human fixations. © 2011 IEEE.

关键词： Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Particle swarm optimization for automatic parameters determination of pulse coupled neural network

引用

Journal of Computers 2011年第8期6卷 1546-1553页

作者： Xinzheng, Xu Shifei, Ding Zhongzhi, Shi Zuopeng, Zhao Hong, Zhu School of Computer Science and Technology China University of Mining and Technology Xuzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Pulse coupled neural network (PCNN), a wellknown class of neural networks, has original advantage when applied to image processing because of its biological background. However, when PCNN is used, the main problem is that its parameters aren't self-adapting according to different image which limits the application range of PCNN. Considering that, this paper proposed a new method based on particle swarm optimization (PSO) to determine automatically the parameters of PCNN. In this method, the algorithm of PSO is applied to search automatically optimum in the solution space of PCNN's parameters until finding global optimal solution. Experimental results demonstrate that the proposed method is accurate and robust for image segmentation, and its performance is better than the methods of Otsu, manual adjustment of parameters when mutual information is adopted as evaluation criteria. © 2011 ACADEMY PUBLISHER.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

A rough RBF neural networks optimized by the genetic algorithm

引用

Advances in information Sciences and Service Sciences 2011年第7期3卷 332-339页

作者： Ding, Shifei Ma, Gang Xu, Xinzheng School of Computer Science and Technology China University of Mining and Technology Xuzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing China

The large-scale data parallelism processing is an inherent characteristic of artificial neural networks, but the networks bring the efficiency problems of data processing. As one of the artificial neural networks, Radial Basis Function (RBF) neural networks have the same problem. Therefore, how to reduce the scale of data to improve the efficiency of data processing has been a hot issue among the artificial intelligence scholars. Based on the traditional RBF neural networks, this paper puts forward a method which determines the important degree of the sample attributes based on knowledge entropy of Rough set by analyzing the relationship between the knowledge entropy and the weight of the sample attributes, and assesses the importance of the sample attributes between the input layer and the hidden layer, namely the attribution reduction, so as to achieve reduce the scale of data processing. The ultimate aim of training RBF neural networks is to seek a set of suitable networks parameters which makes the sample output error achieve the minimum or required accuracy, while Genetic Algorithm (GA) has the properties of finding out the optimal solution through multiplepoint random search in the solution space, so Genetic Algorithm is used to optimize the centers, the widths and the weights between the hidden layer and the output layer of RBF neural networks in training the networks. Finally, a model about A Rough RBF Neural Networks Optimized by the Genetic Algorithm (GA-RS-RBF) is proposed in this paper. The simulation results show that the rough RBF neural network optimized by the Genetic Algorithm is better than the traditional RBF neural networks in classification about Iris datasets.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Fast intra mode selection for stereo video coding using epipolar constraint

Fast intra mode selection for stereo video coding using epip...

引用

IEEE Visual Communications and Image Processing (VCIP)

作者： Guolei Yang Luhong Liang Wen Gao Peking University Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

Application of stereo video in TV industry and consumer electronics becomes very popular recently. Thus, fast algorithm for stereo video coding is highly desired because of its huge inter-view computational redundancy. In our previous work we proposed an epipolar constraint based fast inter mode selection for stereo video using motion vector of blocks as a indicator of similarity, nevertheless, intra mode selection is also highly complex in standards like H.264/AVC. In this paper, a practical fast intra mode selection is proposed to eliminate the computational redundancy by exploiting inter-view dependency based on epipolar constraint. The proposed method does not rely on disparity estimation. Instead, a sliding window is employed to generate an intra mode candidate pool from macro-blocks on the epipolar line. The candidate pool is then rectified to remove invalid modes and improve accuracy. Finally, optimal prediction mode is selected from the candidate pool. The proposed method can significantly reduce the number of mode candidates/prediction directions compared to exhaustive mode selection by 79%. Experiments on 5 HD video coded in 1-frame demonstrate the overall coding time of one view is saved by 56% on average, with slightly video quality loss less than 0.1 dB.

关键词： Encoding Prediction algorithms Redundancy Signal processing algorithms Video coding Estimation Complexity theory

来源：评论

学校读者我要写书评

暂无评论

Parallel Outlier Detection Using KD-Tree Based on MapReduce

Parallel Outlier Detection Using KD-Tree Based on MapReduce

引用

IEEE International Conference on Cloud computing technology and Science (CloudCom)

作者： Qing He Yunlong Ma Qun Wang Fuzhen Zhuang Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing China Chinese Academy of Sciences Beijing China

Distributed and Parallel algorithms have attracted a vast amount of interest and research in recent decades, to handle large-scale data set in real-world applications. In this paper, we focus on a parallel implementation of KD-Tree based outlier detection method to deal with large-scale data set. As one of the state-of-the-art outlier detection methods, KD-Tree based has been approved to be an effective algorithm. However, it still cannot process large-scale data set efficiently due to its serial implementation. Based on the current and powerful parallel programming framework -- MapReduce, we propose to implement the parallel KD-Tree based outlier detection algorithm (e.g., PKDTree for short). Experimental results demonstrate the efficiency of PKDTree according to the evaluation criterions of scale up, speedup and size up.

关键词： Smoothing methods Parallel algorithms Computers Arrays Detection algorithms Algorithm design and analysis Runtime

来源：评论

学校读者我要写书评

暂无评论

The Estimation of Winter Wheat Yield Based on MODIS Remote Sensing Data

The Estimation of Winter Wheat Yield Based on MODIS Remote S...

引用

Computer and computing Technologies in Agriculture V——5th IFIP TC 5/SIG 5.1 Conference(CCTA2011) Part II

作者： Linsheng Huang Qinying Yang Dong Liang Yansheng Dong Xingang Xu Wenjiang Huang Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University Beijing Research Center for Information Technology in Agriculture

ISBN: (纸本)9783642272776

A yield estimation method by remote sensing was used to estimate the yield of winter wheat in Jiangsu province,*** first step of this study was to extract the planting area of winter wheat from environmental satellite images and land-use map of Jiangsu province,meanwhile,correlation analyses were performed by using 8-day of composite Leaf Area Index(LAI)data from Moderate Resolution Imaging Spectroradiometer(MODIS)and statistical yield of corresponding ***,the average LAI was calculated at the optimal growth period,and the statistical yields of wheat for all counties were collected,in which the former was chosen as the independent variable and the latter was the dependent variable,and the regression model was ***,the accuracy and stability of the regression model were validated using the data of another *** results indicated that the yield estimation model at provincial level was reliable,the Root Mean Square Error(RMSE)and the Mean Absolute Error(MAE)of the model was 12.1%and 9.7%,*** addition,the yield estimation system of winter wheat in Jiangsu province was constructed and published based on ArcMap and ArcGIS Server.

关键词： LAI remote sensing yield estimation regression model ArcGIS Server

来源：评论

学校读者我要写书评

暂无评论

Context-specific miRNA regulation network predicts cancer prognosis

Context-specific miRNA regulation network predicts cancer pr...

引用

5th IEEE International Conference on Systems Biology, ISB 2011

作者： Zhou, Xionghui Liu, Juan Liu, Changning Rayner, Simon Liang, Fengji Ju, Jingfang Li, Yinghui Chen, Shanguang Xiong, Jianghui School of Computer Science Wuhan University Wuhan China Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China State Key Laboratory of Virology Wuhan Institute of Virology Chinese Academy of Sciences Wuhan China Department of Pathology Stony Brook University Medical Center NY United States

ISBN: (纸本)9781457716669

MicroRNAs can regulate hundreds of target genes and play a pivotal role in a broad range of biological process. However, relatively little is known about how these highly connected miRNAs-target networks are remodelled in the context of various diseases. Here we examine the dynamic alteration of context-specific miRNA regulation to determine whether modified microRNAs regulation on specific biological processes is a useful information source for predicting cancer prognosis. A new concept, Context-specific miRNA activity (CoMi activity) is introduced to describe the statistical difference between the expression level of a miRNA's target genes and non-targets genes within a given gene set (context). The microarray gene expression profile of brain tumors from 356 patients (The Cancer Genome Atlas dataset) was converted into a CoMi activity pattern, and showed significant positive correlation with the corresponding miRNA expression pattern. In a breast cancer cohort, the differential CoMi activity between good prognosis (longer survival) vs. bad prognosis patients forms a scale-free network, which highlighted a group of important cancer-related microRNAs and GO terms, e.g. hsa-miR-34a and 'cell adhesion'. Then two breast cancer cohorts were used in outcome prediction in an independent test. Using a popular T-test feature selection method and a support vector machine (SVM) classifier with 10-fold cross-validation, the CoMi activity feature achieves an area under curve (AUC) of 0.7155, better than the AUC value of 0.6339 for feature selection based on mRNA expression. In an independent test, CoMi feature selection achieved an AUC of 0.6874. Survival analysis also shows signatures defined by CoMi activity was predictive of survival and superior to mRNAs signatures. In short, we have demonstrated the first interrogation of dynamic remodeling of context specific miRNAs regulation networks in cancer. The altered microRNAs regulation on specific contexts could be used to predi

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

China's grain security warning based on multifactor information fusion

引用

Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering 2011年第5期27卷 183-189页

作者： Su, Xiaoyan Zhang, Huijie Li, Zhiqiang Deng, Yong School of Electronics and Information Technology Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of Digital Agricultural Early-warning Technology Ministry of Agriculture of China Beijing 100081 China College of Computer and Information Sciences Southwest University Chongqing 400715 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan 411105 China

China is the largest food consumption country in the world. With the social and economic development, China's food security has become a global attention. Grain security research involves many uncertain factors: as well as quantitative and qualitative information. In order to get the grain security status comprehensively, we proposed a method to evaluate risk in grain security based on multifactor information fusion. In the method, the quantitative and qualitative information were used to construct the basic probability assignment, and the attribute weights was got based on the Analytic Hierarchy Process method. After that, the multifactor fusion results were got based on the Dempster combination rule. The effectiveness of the method was verified with a numeric example that the data comes from the yearbook of China in 2007. The Results show that the method is effective and can correctly reflect the grain safety warning degrees.

关键词： Analytic hierarchy process

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：