检索结果-内蒙古大学图书馆

A new query dependent feature fusion approach for medical image retrieval based on one-class SVM

Journal of Computational Information Systems 2011年第3期7卷 654-665页

作者： Huang, Yonggang Ma, Dianfu Zhang, Jun Zhao, Yongwang Yi, Shengwei Institute of Advanced Computing Technology BeiHang University Beijing China National Lab. of Software Development Environment BeiHang University Beijing China School of Computer Science and Software Engineering University of Wollongong Wollongong Australia

With the development of the internet, medical images are now availab.e in large numbers in online repositories, and there exists the need to retrieval the medical images in the content-based ways through automatically extracting visual information of the medical images. Since a single feature extracted from images just characterizes certain aspect of image content, multiple features are necessarily employed to improve the retrieval performance. Furthermore, a special feature is not equally important for different image queries since a special feature has different importance in reflecting the content of different images. However, most existed feature fusion methods for image retrieval only utilize query independent feature fusion or rely on explicit user weighting. In this paper, based on multiply query samples provided by the user, we present a novel query dependent feature fusion method for medical image retrieval based on one class support vector machine. The proposed query dependent feature fusion method for medical image retrieval can learn different feature fusion models for different image queries, and the learned feature fusion models can reflect the different importance of a special feature for different image queries. The experimental results on the IRMA medical image collection demonstrate that the proposed method can improve the retrieval performance effectively and can outperform existed feature fusion methods for image retrieval. Copyright © 2011 Binary Information Press.

关键词： Image retrieval

来源：评论

学校读者我要写书评

暂无评论

Color-mood-aware clothing re-texturing

Color-mood-aware clothing re-texturing

引用

12th International Conference on Computer-Aided Design and Computer Graphics, CAD/Graphics 2011

作者： Shen, Jianbing Sun, Hanqiu Mao, Xiaoyang Guo, Yanwen Jin, Xiaogang Beijing Laboratory of Intelligent Information Technology School of Computer Science Beijing Institute of Technology Beijing 100081 China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Hong Kong University of Yamanashi Japan National Key Lab. for Novel Software Technology Nanjing University China State Key Lab. of CAD and CG Zhejiang University Hangzhou 310027 China

ISBN: (纸本)9780769544977

In this paper, we present a novel color-mood-aware technique to re-texture clothing in a photograph. An efficient classification algorithm is developed to classify clothing textures using color mood scheme. To re-texture the clothing, our approach first computes the gradient maps for the cloth region to be replaced and then calculates the texture distortion coordinates on the projected cloth region according to the gradient maps. After the user selects a target clothing texture from the classified clothing texture database, the lighting and shading effects on the original photograph is transferred using the HSV color space. Experimental results show that the proposed approach successfully re-textures the clothes in photographs while preserving the geometry and lighting features. © 2011 IEEE.

关键词： Color

来源：评论

学校读者我要写书评

暂无评论

A kind of SND-based algorithm for self-adapting network congestion control

引用

Journal of Information and Computational Science 2011年第11期8卷 2033-2044页

作者： Zhang, Degan Hu, Yuxia Liang, Yanpin Liu, Zhaojing Tianjin Key Lab. of Intelligent Computing and Novel software Technology Tianjin University of Technology Tianjin 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300191 China

A kind of SND-based algorithm for self-adapting network congestion control has been presented in this paper, which is for the complicated and integrated network environment that the Internet of Things (IOT) to face in the future. As we know, the control of network congestion has become a hot spot in the study of Internet of Things transmission service. The network control algorithm of self-adapting congestion based on semi-normal distribution has improved the original packet loss rate function, and changed congestion situation in Internet of Things. By our many experiments, the validity and correctness of this algorithm has been tested. © 2011 Binary Information Press.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

A novel framework of online network coding for multicast switches with constrained buffers

引用

Journal of Electronics 2011年第4期28卷 460-467页

作者： Wang, Wei Yu, Li Zhu, Guangxi Li, Hui Wuhan National Lab. for Optoelectronics Division of Communiction and Intelligent Networks Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan 430074 China Shenzhen Key Lab of Cloud Computing Technology and Application Shenzhen Graduate School Peking University Shenzhen 518055 China Department of Electronics and Information Engineering Huazhong University of Science and Technology Wuhan 430074 China

Network coding is able to address output conflicts when fanout splitting is allowed for multicast switching. Hence, it successfully achieves a larger rate region than non-coding approaches in crossbar switches. However, network coding requires large coding buffers and a high computational cost on encoding and decoding. In this paper, we propose a novel Online Network Coding framework called Online NC for multicast switches, which is adaptive to constrained buffers. Moreover, it enjoys a much lower decoding complexity O(n ²) by a Vandermonde matrix based approach, as compared to conventional randomized network coding O(n ³). Our approach realizes online coding with one coding algorithm that synchronizes buffering and coding. Therefore, we significantly reduce requirements on buffer space, while also sustaining high throughputs. We confirm the superior advantages of our contributions using empirical studies. © 2011 Science Press, Institute of Electronics, CAS and Springer-Verlag Berlin Heidelberg.

关键词： Multicast Network coding Packet switching Vandermonde matrix

来源：评论

学校读者我要写书评

暂无评论

A topic model of observing Chinese characters

A topic model of observing Chinese characters

引用

International Conference on intelligent Human-Machine Systems and Cybernetics

作者： Zhang, Yunkai Qin, Zengchang College of Software Beihang University Beijing 100191 China Intelligent Computing and Machine Learning Lab. School of Automation Science and Electrical Engineering Beihang University 100191 China

ISBN: (纸本)9780769541518

The Topic Models are a class of hierarchical statistical models for analyzing document collections and it has become one of the most used techniques in Natural Language Processing in the recent years. It assumes that each document could be expressed as a mixture of topics and each topic could be characterized by a distribution over words. In previous research [6], like in English language, Topic Models for Chinese Language use the words as observing data. In this research, we demonstrated the effectiveness of using Chinese characters as the basic units of observing data. The comparisons with those models based on Chinese words and English words are presented. © 2010 IEEE.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Hierarchical clustering of 3-D line segments for building detection

Hierarchical clustering of 3-D line segments for building de...

引用

作者： Park, Dong-Chul Intelligent Computing Research Lab. Dept. of Electronics Engineering Myong Ji University Korea Republic of

ISBN: (纸本)9781424499908

A novel approach for an efficient extraction of rectangular boundaries from aerial image data is proposed in this paper. In this approach, a Centroid Neural Network (CNN) with a metric of line segments is utilized for connecting lowlevel linear structures or grouping similar objects. The proposed an approach, called hierarchical clustering method, utilizes the fact that rooftops of a building are about the same height and perform clustering process with candidate 3-D line segments with similar heights. Experiments are performed with a set of high resolution satellite image data. The results show that the proposed hierarchical clustering method can remove noisy segments such as shade lines efficiently and find more accurate rectangular boundaries. © 2011 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Intuitive fuzzy c-means algorithm for MRI segmentation

Intuitive fuzzy c-means algorithm for MRI segmentation

引用

2010 International Conference in Information Science and Applications, ICISA 2010

作者： Park, Dong-Chul Intelligent Computing Research Lab. Dept. of Electronics Engineering Myong Ji University Yong In Korea Republic of

ISBN: (纸本)9781424459438

A new model called intuitive fuzzy c-means (IFCM) model is proposed for the segmentation of magnetic resonance image in this paper. Fuzzy c-means (FCM) is one of the most widely used clustering algorithms and assigns memberships to which are inversely related to the relative distance to the point prototypes that are cluster centers in the FCM model. In order to overcome the problem of outliers in data, several models including possibilistic c-means (PCM) and possibilistic-fuzzy c-means (PFCM) models have been proposed. In IFCM, a new measurement called intuition level is introduced so that the intuition level helps to alleviate the effect of noise. Several numerical examples are first used for experiments to compare the clustering performance of IFCM with those of FCM, PCM, and PFCM. A practical magnetic resonance image data set is then used for image segmentation experiment. Results show that IFCM compares favorably to several clustering algorithms including the SOM, FCM, CNN, PCM, and PFCM models. Since IFCM produces cluster prototypes less sensitive to outliers and to the selection of involved parameters than the other algorithms, IFCM is a good candidate for data clustering and image segmentation problems. ©2010 IEEE.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

A time series data prediction scheme using bilinear recurrent neural network

A time series data prediction scheme using bilinear recurren...

引用

2010 International Conference in Information Science and Applications, ICISA 2010

作者： Park, Dong-Chul Intelligent Computing Research Lab. Dept. of Electronics Engineering Myong Ji University Yong In Korea Republic of

ISBN: (纸本)9781424459438

A time series prediction method based on a BiLinear Recurrent Neural Network (BLRNN) is proposed in this paper. The proposed predictor is based on the BLRNN that has been proven to have robust abilities in modeling and predicting time series. The learning process is further improved by using a multiresolution-based learning algorithm for training the BLRNN so as to make it more robust for the prediction of time series data. The proposed multiresolution-based BLRNN predictor is applied to the long-term prediction of time series data sets. Experiments and results on the Mackey-Glass Series data and Sunspot Series data show that the proposed prediction scheme outperforms both the traditional MultiLayer Perceptron Type Neural Network (MLPNN) and the BLRNN in terms of the normalized mean square error (NMSE). ©2010 IEEE.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Application of pruned bilinear recurrent neural network to load prediction

Application of pruned bilinear recurrent neural network to l...

引用

2010 ACS/IEEE International Conference on Computer Systems and Applications, AICCSA 2010

作者： Kim, Jae-Young Park, Dong-Chul Woo, Dong-Min Intelligent Computing Research Lab. Dept. of Electronics Engineering Myong Ji University Yong In Korea Republic of

ISBN: (纸本)9781424477159

Prediction of electric load by using Pruned Bilinear Recurrent Neural Network (PBRNN) is proposed and presented in this paper. The PBRNN was developed to alleviate the computational cost associated with the Bilinear Recurrent Neural Network by using a pruning procedure. Since electric loads have a time-series characteristic, a prediction scheme based on the PBRNN can be an optimal candidate for the electric load prediction problem. Experiments are conducted on a load data set from the North-American Electric Utility (NAEU). Results show that the Pruned BRNN-based prediction scheme outperforms the conventional Multi-Layer Perceptron Type Neural Network (MLPNN) in terms of the Mean Absolute Percentage Error(MAPE).

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Classification of audio data using a centroid neural network

Classification of audio data using a centroid neural network

引用

2010 International Conference in Information Science and Applications, ICISA 2010

作者： Park, Dong-Chul Intelligent Computing Research Lab. Dept. of Electronics Engineering Myong Ji University Yong In Korea Republic of

ISBN: (纸本)9781424459438

The automatic classification of audio data is an effective way to organize a large-scale audio data files. In this paper, an automatic content-based audio classification model using Centroid Neural Networks (CNN) with a Divergence Measure is proposed. The Divergence-based Centroid Neural Network (D-CNN) algorithm, which employs the divergence measure as its distance measure, is used for clustering of Gaussian Probability Distribution Function (GPDF) data. In comparison with other conventional algorithms, the D-CNN designed for probability data has the robustness advantages of utilizing a audio data representation method in which each audio data is represented by a Gaussian distribution feature vector. Experiments and results show that the proposed classification model very compatible classification accuracy with classical models employing the conventional k-means and CNN algorithms. ©2010 IEEE.

关键词： Distribution functions

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：