检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

114 篇 会议
32 篇 期刊文献

馆藏范围

146 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

75 篇 工学
- 59 篇 计算机科学与技术...
- 55 篇 软件工程
- 24 篇 控制科学与工程
- 16 篇 信息与通信工程
- 10 篇 生物工程
- 8 篇 光学工程
- 7 篇 生物医学工程（可授...
- 5 篇 化学工程与技术
- 3 篇 机械工程
- 3 篇 仪器科学与技术
- 2 篇 电气工程
- 2 篇 电子科学与技术（可...
- 2 篇 建筑学
- 2 篇 土木工程
- 1 篇 力学（可授工学、理...
55 篇 理学
- 27 篇 数学
- 17 篇 物理学
- 12 篇 统计学（可授理学、...
- 11 篇 生物学
- 6 篇 系统科学
- 5 篇 化学
- 3 篇 地球物理学
- 2 篇 天文学
31 篇 管理学
- 20 篇 管理科学与工程(可...
- 14 篇 图书情报与档案管...
- 2 篇 工商管理
6 篇 医学
- 6 篇 临床医学
- 5 篇 基础医学(可授医学...
- 5 篇 药学(可授医学、理...
1 篇 文学
- 1 篇 新闻传播学
1 篇 艺术学

主题

24 篇 feature extracti...
12 篇 training
11 篇 support vector m...
11 篇 pattern recognit...
11 篇 principal compon...
9 篇 neural networks
9 篇 histograms
9 篇 kernel
8 篇 image processing
8 篇 remote sensing
7 篇 electroencephalo...
6 篇 discrete wavelet...
5 篇 face recognition
5 篇 scattering
5 篇 independent comp...
5 篇 algorithm design...
5 篇 bayesian methods
5 篇 feedforward neur...
5 篇 image analysis
5 篇 robustness

机构

74 篇 image processing...
13 篇 school of comput...
9 篇 laboratory of im...
5 篇 university of ch...
4 篇 school of inform...
3 篇 image processing...
3 篇 national laborat...
3 篇 department of au...
3 篇 the school of co...
3 篇 school of comput...
3 篇 college of infor...
3 篇 image processing...
3 篇 image processing...
3 篇 image processing...
3 篇 institute of ima...
3 篇 image processing...
2 篇 school of founda...
2 篇 tampereen yliopi...
2 篇 image processing...
2 篇 institute for as...

作者

68 篇 ping guo
31 篇 guo ping
25 篇 qian yin
11 篇 xin zheng
11 篇 yin qian
7 篇 hassan dawood
6 篇 hussain dawood
5 篇 bingxin xu
5 篇 xinyu chen
4 篇 zheng xin
4 篇 jing wang
4 篇 xu anbang
4 篇 anbang xu
3 篇 fang tao
3 篇 rukun hu
3 篇 liu cheng-lin
3 篇 xu bingxin
3 篇 duan fuqing
3 篇 fuqing duan
3 篇 wang hongfeng

语言

144 篇 英文
2 篇 中文

检索条件"机构=Image Processing and Pattern Recognition Laboratory Beijing Normal University"

共 146 条记录，以下是51-60 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

A fusion method for multispectral and panchromatic images based on HSI and Contourlet transformation

A fusion method for multispectral and panchromatic images ba...

引用

International Workshop on image Analysis for Multimedia Interactive Services, WIAMIS

作者： Mengxin Song Xinyu Chen Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

Fusion of multispectral and panchromatic remote sensing images is a procedure to obtain spatial resolution and quality of the panchromatic image as well as preserving spectral information of the multispectral image. In this paper, we present a new fusion method based on HSI (Hue-Saturation-Intensity) and Contourlet transform. First, we convert the multispectral image from the RGB color space into the HSI color space. Then, by applying Contourlet transform to the panchromatic image and the I component of the multispectral image, we utilize an improved fusion rule based on PCA for the low-frequency sub-images, and engage the maximum fusion rule for the high-frequency sub-images. Finally, a fusion image is obtained by the inverse HSI transform. The experimental results show that the proposed fusion method not only enhances the spatial resolution of the fusion image, but also preserves the spectral information of the original multispectral image.

关键词： Spatial resolution Principal component analysis Multispectral imaging Wavelet transforms Remote sensing Frequency Discrete wavelet transforms image resolution Fuses Fourier transforms

来源：评论

学校读者我要写书评

暂无评论

Removal of random-valued impulse noise by Khalimsky grid

Removal of random-valued impulse noise by Khalimsky grid

引用

Asia Pacific Conference on Multimedia and Broadcasting (APMediaCast)

作者： Hussain Dawood Hassan Dawood Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

In this paper, based on Khalimsky grid, a new Random-valued Impulse noise identification and removal method is proposed. Khalimsky grid can presents the neighborhood relationship among the pixels in the sliding window, effectively. The local statistics of Khalimsky grid is used to define an adaptive threshold range to identify the central pixel in current sliding window as noisy or noise free in an iterative way. The identified noisy pixel is replaced by local statistics of propose vertical direction based noise removal method. The performance of the propose method is evaluated on different test images and compared with state-of-the-art methods. Experimental results show that the propose method can identify the impulse noise, as well as can preserve the detailed information of an image, efficiently.

关键词： Noise Noise measurement Tin Multimedia communication Filtering algorithms Asia Digital multimedia broadcasting

来源：评论

学校读者我要写书评

暂无评论

Comparison of linear dimensionality reduction methods in image annotation

Comparison of linear dimensionality reduction methods in ima...

引用

International Workshop on Advanced Computational Intelligence (IWACI)

作者： Shiqiang Li Hussain Dawood Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

Dimension reduction methods are often used to analyzing high dimensional data, linear dimension methods are commonly used due to their simple geometric interpretations and for effective computational cost. Dimension reduction plays an important role for feature selection. In this paper, we have given a detailed comparison of state-of-the-art linear dimension reduction methods like principal component analysis (PCA), random projections (RP), and locality preserving projections (LPP). We have determined which dimension reduction method performs better under the FastTag image annotation framework. Experiments are conducted on three standard bench mark image datasets such as CorelSk, IAPRTC-12 and ESP game to compare the efficiency, effectiveness and also memory usage. A detailed comparison among the aforementioned dimension reduction method is given.

关键词： Principal component analysis Benchmark testing Kernel Random access memory Customer relationship management

来源：评论

学校读者我要写书评

暂无评论

Complete two-dimensional principal component analysis for image registration

Complete two-dimensional principal component analysis for im...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Anbang Xu Xinyu Chen Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

We present a new feature extraction method, which called the complete two-dimensional principal component analysis (Complete 2DPCA), for image registration. Complete 2DPCA is based on 2D image matrices. Two image covariance matrices are constructed directly using the original image matrix and their eigenvectors are derived for image feature extraction. In the 2D image registration scheme, we propose complete 2DPCA to extract features from the image sets, and these features are input vectors of feedforward neural networks (FNN). Neural network outputs are registration parameters with respect to reference and observed image sets. Comparative experiments are performed between complete 2DPCA based method and other feature based methods. The results show that the proposed method has an encouraging performance.

关键词： Principal component analysis image registration Feature extraction Neural networks Covariance matrix Feedforward neural networks Intelligent robots Registers Discrete cosine transforms image processing

来源：评论

学校读者我要写书评

暂无评论

Software Fault Prediction Framework Based on aiNet Algorithm

Software Fault Prediction Framework Based on aiNet Algorithm

引用

International Conference on Computational Intelligence and Security

作者： Qian Yin Ruiyi Luo Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

Software fault prediction techniques are helpful in developing dependable software. In this paper, we proposed a novel framework that integrates testing and prediction process for unit testing prediction. Because high fault prone metrical data are much scattered and multi-centers can represent the whole dataset better, we used artificial immune network (aiNet) algorithm to extract and simplify data from the modules that have been tested, then generated multi-centers for each network by Hierarchical Clustering. The proposed framework acquires information along with the testing process timely and adjusts the network generated by aiNet algorithm dynamically. Experimental results show that higher accuracy can be obtained by using the proposed framework.

关键词： Software Prediction algorithms Testing Software algorithms Measurement Clustering algorithms Accuracy

来源：评论

学校读者我要写书评

暂无评论

Residual Error based Approach to Classification of Multisource Remote Sensing images

Residual Error based Approach to Classification of Multisour...

引用

International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Dongdong Cao Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

Classification of multisource remote sensing images has been studied for decades, and many methods have been proposed. Most of these studies focus on how to improve the classifiers in order to obtain higher classification accuracy. However, as we know, even if the most promising neural network method, its good performance not only depends on the classifier itself, but also has relation to the training pattern (i.e. features). On consideration of this aspect, we propose an approach to feature selection and classification of multisource remote sensing image based on residual error in this paper. In particular, a feature-selection scheme approach is proposed, which is to select effective subsets of features as inputs of a classifier by taking into account the residual error associated with each land-cover class. In addition, a classification technique base on selected features by using a feedforward neural network is investigated. The results of experiments carried out on a multisource data set confirm the validity of the proposed approach

关键词： Remote sensing Neural networks Remote monitoring Earth Feedforward neural networks Computer errors Classification algorithms Bayesian methods Robustness image processing

来源：评论

学校读者我要写书评

暂无评论

Text-independent Speaker Identification Using Fisher Discrimination Dictionary Learning Method

Text-independent Speaker Identification Using Fisher Discrim...

引用

International Conference on Computational Intelligence and Security

作者： Xia Wang Qian Yin Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

In last decades, text-independent speaker recognition is a hot research topic attracted many researchers. In this paper, we proposed to apply the Fisher discrimination dictionary learning method to identify the text-independent speaker recognition. The feature used in classification is the Gaussian Mixture Model super vector. The proposed method is evaluated with public ally available dataset TIMIT. Experimental results show that the proposed method outperforms the Sparse Representation Classifier used for text-independent speaker recognition in both clean and noisy condition.

关键词： Dictionaries Mathematical model Equations Speaker recognition Noise measurement Learning systems pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Large Scale Terrain Compression and Real-Time Rendering Based on Wavelet Transform

Large Scale Terrain Compression and Real-Time Rendering Base...

引用

International Conference on Computational Intelligence and Security

作者： Xiaodong Wang Xin Zheng Qian Yin Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9781424441969

By taking advantage of 3 attributes of integer wavelet transform (IWT): efficient computing, multi-resolution and partially reconstruction, we propose one lossless large scale terrain compression method with high compression rate in this paper. By this way, we can decompress terrain data with multi-resolution efficiently at any viewpoint and render the terrain in real time by fast updating strategy. Experiments prove that by our method we can compress the data efficiently and render the terrain scene smoothly in real time.

关键词： Large-scale systems Wavelet transforms image coding Rendering (computer graphics) image reconstruction Discrete wavelet transforms image resolution Multiresolution analysis Virtual reality Computational intelligence

来源：评论

学校读者我要写书评

暂无评论

Sparse Representation for Multi-Label image Annotation

Sparse Representation for Multi-Label Image Annotation

引用

International Conference on Computational Intelligence and Security

作者： Bingxin Xu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9781457720086

image annotation is the process of assigning proper keywords to describe the content of a given image, which can be regarded as a problem of multi-object image classification. In this paper, a general multi-label annotation algorithm is proposed, which is based on sparse representation theory and employs a multi-level decision method to deal with the multi-object classification problem. The experimental results show that the proposed algorithm can provide more promising results compared with the traditional classification based image annotation methods.

关键词： Training Vectors Support vector machines Databases Feature extraction Roads Training data

来源：评论

学校读者我要写书评

暂无评论

A Hierarchical Model with Pseudoinverse Learning Algorithm Optimazation for Pulsar Candidate Selection

A Hierarchical Model with Pseudoinverse Learning Algorithm O...

引用

Congress on Evolutionary Computation

作者： Shijia Li Sibo Feng Ping Guo Qian Yin Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

Pulsars search has always been one of the most concerned problem in the field of astronomy. Nowadays, with the development of astronomical instruments and observation technology, the amount of data is getting bigger and bigger. Radio pulsar surveys have generated and will generate vast amounts of data. To handle big data, developing new technologies and frameworks to efficiently and accurately analyze these data become increasing urgent. The number of positive and negative samples in pulsar candidate data set is very unbalanced, if we only use these a few positive samples to train a deep neural network (DNN), the trained DNN is prone because of the problem of overfitting and will affect the generalization ability. Motivated by the mixtures of experts network architecture, we proposed a hierarchical model for pulsar candidate selection which assembles a set of trained base classifiers. Moreover, training a neural network always takes a lot of time because of using gradient descent (GD) based algorithm. In this work, we utilize the pseudoinverse learning algorithm instead of GD based algorithm to train proposed model. With the designed network architecture and adopted training algorithm, our model has the advantages not only with high steady-state precision but also good generalization performance.

关键词： Matrix decomposition Training Big Data Neural networks Task analysis Decoding Machine learning

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共15页 << < 2 3 4 5 6 7 8 9 10 11 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：