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

87 篇 会议
48 篇 期刊文献
1 册 图书

馆藏范围

136 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

82 篇 工学
- 55 篇 计算机科学与技术...
- 49 篇 软件工程
- 20 篇 光学工程
- 20 篇 信息与通信工程
- 20 篇 生物医学工程（可授...
- 16 篇 控制科学与工程
- 14 篇 电子科学与技术（可...
- 13 篇 生物工程
- 12 篇 电气工程
- 8 篇 机械工程
- 5 篇 仪器科学与技术
- 4 篇 化学工程与技术
- 2 篇 交通运输工程
- 1 篇 力学（可授工学、理...
- 1 篇 冶金工程
49 篇 理学
- 31 篇 数学
- 16 篇 物理学
- 15 篇 生物学
- 12 篇 统计学（可授理学、...
- 5 篇 化学
- 5 篇 系统科学
27 篇 管理学
- 15 篇 图书情报与档案管...
- 13 篇 管理科学与工程(可...
- 2 篇 工商管理
9 篇 医学
- 7 篇 临床医学
- 6 篇 基础医学(可授医学...
- 6 篇 药学(可授医学、理...
3 篇 艺术学
- 3 篇 设计学（可授艺术学...
2 篇 教育学
- 2 篇 教育学
1 篇 法学
- 1 篇 社会学
1 篇 军事学

主题

16 篇 pattern recognit...
16 篇 image processing
10 篇 feature extracti...
9 篇 support vector m...
7 篇 computer science
7 篇 image segmentati...
7 篇 laboratories
7 篇 image analysis
6 篇 machine learning
6 篇 image recognitio...
6 篇 computer vision
5 篇 image edge detec...
5 篇 accuracy
5 篇 robustness
4 篇 blood vessels
4 篇 data mining
4 篇 image coding
4 篇 histograms
4 篇 testing
4 篇 information scie...

机构

21 篇 image processing...
13 篇 institute of ima...
13 篇 school of comput...
6 篇 pattern recognit...
6 篇 faculty of compu...
5 篇 pattern recognit...
4 篇 college of compu...
4 篇 laboratory of im...
4 篇 pattern recognit...
4 篇 school of comput...
3 篇 institute of med...
3 篇 the school of co...
3 篇 school of comput...
3 篇 shanghai jiao to...
3 篇 key laboratory o...
3 篇 shanghai key lab...
3 篇 faculty of scien...
3 篇 key laboratory o...
2 篇 college of compu...
2 篇 university of sc...

作者

18 篇 ping guo
11 篇 yang jie
9 篇 guo ping
8 篇 yang yang
6 篇 qian yin
6 篇 gong chen
5 篇 huang xiaolin
5 篇 leonardis aleš
4 篇 h. bischof
4 篇 aniati murni ary...
4 篇 bischof horst
4 篇 wang lihui
4 篇 shen hong-bin
4 篇 a. leonardis
4 篇 huang qian
3 篇 jie yang
3 篇 rukun hu
3 篇 qin yulei
3 篇 lu yue
3 篇 a.k. jain

语言

132 篇 英文
3 篇 其他
1 篇 中文

检索条件"机构=Image Processing and Pattern Recognition Laboratory Faculty of Computer Science"

共 136 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：

An Evaluation of Low Cost Scanning versus Industrial 3D Scanning Devices

An Evaluation of Low Cost Scanning versus Industrial 3D Scan...

引用

Congress on image and Signal processing, CISP

作者： Miha Drenik Martin Kampel Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Pattern Recognition and Image Processing Group Technical University of of Vienna Vienna Austria

This paper presents an evaluation of two different 3D scanning devices. They can be put into operation depending on the monetary constraints of the user on one hand, and the accuracy needed for a specific application on the other hand. The setting up of the systems and the process of scanning with the devices are presented. Two setups were formed to evaluate the capabilities of a low costs scanning device together with industrial scanning devices. A comparison of the scans obtained was made by using a Konica Minolta VI-9i industrial scanning solution as a reference. The analysis comprises the estimation of surface flatness, the evaluation of measuring of geometric shapes, and the appraisal of the time required for obtaining a virtual 3D representation of a scanned object. The results show that both the curves as well as the shapes as a whole have been captured accurately.

关键词： Costs Shape measurement Application software Feeds Signal processing computer industry Information science pattern recognition image processing Time measurement

来源：评论

学校读者我要写书评

暂无评论

RBP-Former: Joint Prediction of RNA-protein Binding Sites on Full-length RNA Transcripts for Multiple RBPs

RBP-Former: Joint Prediction of RNA-protein Binding Sites on...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Li, Yichong Liu, Xiaojian Cheng, Fan Pan, Xiaoyong Yang, Yang Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai200240 China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai200240 China

ISBN: (纸本)9798350386226

RNA-binding proteins (RBPs) are essential for gene expression, and the complex RNA-protein interaction mechanisms require analysis of global RNA information. Therefore, accurate prediction of RBP binding sites on full-length RNA transcripts is crucial for understanding these mechanisms and their roles in diseases. While machine learning methods can predict RBP binding to RNA fragments, extending this to full-length transcripts presents challenges due to sequence length and data imbalance. In this paper, we introduce RBP-Former, a binding site joint prediction model designed specifically for full-length RNA transcripts that can be used for multiple RBPs. This model processes information at both coarse and fine-grained levels to fully exploit sequence data and its interactions with multiple RBPs. We develop multi-level imbalance learning strategies, achieving favorable results on imbalanced data. Our method outperforms existing methods in predicting binding sites on full-length RNA transcripts for multiple RBPs, demonstrating its effectiveness in handling imbalanced label and sample distributions. © 2024 IEEE.

关键词： Binding sites

来源：评论

学校读者我要写书评

暂无评论

Ant Colony Optimization Algorithm for Feature Selection and Classification of Multispectral Remote Sensing image

Ant Colony Optimization Algorithm for Feature Selection and ...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Lintao Wen Qian Yin Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

In classification of a multispectral remote sensing image, it is usually difficult to obtain higher classification accuracy if we only consider the image's spectral feature or texture feature alone. In this paper, we present a new approach by applying the Ant Colony Optimization (ACO) algorithm to find a multi-feature vector composed of spectral and texture features in order to get a better result in the classification. The experimental results show that ACO algorithm is helpful in subset searching of the features used to classify the multispectral remote sense image. Using the combination of the spectral and texture features obtained by ACO in classification always produces a better accuracy.

关键词： Ant colony optimization Remote sensing Remote monitoring Multispectral imaging image analysis Data mining Feature extraction Entropy image processing pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Comparative studies of Feature Extraction methods with application to face recognition

Comparative studies of Feature Extraction methods with appli...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Yunfei Jiang Ping Guo Laboratory of Image Processing and Pattern Recognition Beijing Normal University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

In face recognition, the dimensionality of raw data is very high, dimension reduction (feature extraction) should be applied before classification. There exist several feature extraction methods, commonly used are principle component analysis (PCA) and linear discriminant analysis (LDA) techniques. In this paper, we present a comparative study of some feature extraction methods for face recognition in the same conditions. The methods evaluated here include eigenfaces, kernel principal component analysis (KPCA), fisherfaces, direct linear discriminant analysis (D-LDA), regularized linear discriminant analysis (R-LDA), and kernel direct discriminant analysis (KDDA). For the purpose of comparison on feature extraction methods, we adopt nearest neighbor (NN) algorithm from existed classifiers of face recognition, since this classifier is common and simpleness. Empirical studies are conducted to evaluate these feature extraction methods with images from ORL Face Database, and it is found that in most cases LDA-based methods are efficient than PCA-based ones.

关键词： Feature extraction Face recognition Linear discriminant analysis Principal component analysis Kernel pattern recognition Nearest neighbor searches Neural networks Face detection image databases

来源：评论

学校读者我要写书评

暂无评论

Feature data optimization with LVQ technique in semantic image annotation

Feature data optimization with LVQ technique in semantic ima...

引用

International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Ziheng Jiang Jing He Ping Guo School of Computer Science and Technology Beijing Institute of Technology Beijing China Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

In order to improve the classifier performance in semantic image annotation, we propose a novel method which adopts learning vector quantization (LVQ) technique to optimize low level feature data extracted from given image. Some representative vectors are selected with LVQ to train support vector machine (SVM) classifier instead of using all feature data. Performance is compared between the methods with and without feature data optimization when SVM is applied to semantic image annotation. Experiment results show that the proposed method has a better performance than that without using LVQ technique.

关键词： Feature extraction Training Semantics Support vector machine classification Testing Neurons

来源：评论

学校读者我要写书评

暂无评论

Experimental Study of Discriminant Method with Application to Fault-Prone Module Detection

Experimental Study of Discriminant Method with Application t...

引用

International Conference on Computational Intelligence and Security

作者： Gege Guo Ping Guo School of Computer Science and Technology Beijing Institute of Technology Beijing China Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9781424441969

Some techniques have been applied to improving software quality by classifying the software modules into fault-prone or non fault-prone categories. This can help developers focus on some high risk fault-prone modules. In this paper, a distribution-based Bayesian quadratic discriminant analysis (D-BQDA) technique is experimental investigated to identify software fault-prone modules. Experiments with software metrics data from two real projects indicate that this technique can classify software modules into a proper class with a lower misclassification rate and a higher efficiency.

关键词： Fault detection Software quality Support vector machines Support vector machine classification pattern recognition Software metrics Bayesian methods Fault diagnosis Software performance Computational intelligence

来源：评论

学校读者我要写书评

暂无评论

Automatic image analysis of plant root structures

Automatic image analysis of plant root structures

引用

International Conference on pattern recognition

作者： Q. Huang A.K. Jain G.C. Stockman A.J.M. Smucker Department of Computer Science Pattern Recognition and Image Processing Laboratory Department of Crop and Soil Sciences Michigan State University East Lansing MI USA

The minirhizotron technique has provided agricultural scientists the opportunity of observing rhizosphere activities without destroying root structures. Nonetheless, the laborious analysis of the data still prohibits its wide applications. Advanced image understanding techniques are needed to derive satisfactory descriptions of plant root networks in an efficient and robust way. The paper presents a plant root image analysis system designed as a blackboard architecture with a hierarchy of data abstractions. Important properties of plant roots are used throughout the processing and multiple sources of information are combined to resolve uncertainties in image interpretation. Experimental results from some stages of the research are given which support the overall processing scheme.< >

关键词： image analysis Soil image processing Plants (biology) image edge detection Data structures pattern recognition Laboratories computer science Crops

来源：评论

学校读者我要写书评

暂无评论

Kernel ICA applied to feature extraction for image annotation

Kernel ICA applied to feature extraction for image annotatio...

引用

International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Bingxin Xu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China The School of Computer Science and Technology Beijing Institute of Technology Beijing China

In automatic image annotation, it is often extracting low-level visual features from original image for the purpose of mapping to high level image semantic information. In this paper, we propose a novel method which integrates kernel independent component analysis (KICA) and support vector machine (SVM) for analyzing the semantic information of natural images. KICA, which contains a nonlinear kernel mapping component, is adopted to extract low-level features from the original image data. Then these feature vectors are mapped to high-level semantic words using SVM to annotate images with labels in a given semantic label set. Comparative studies have done for the performance of KICA with traditional color histogram and discrete cosine transform features. The experimental results show that the proposed method is capable of extracting the components of images as key features, and with these features to map into semantic categories, higher accuracy is achieved.

关键词： Feature extraction image color analysis Support vector machines Discrete cosine transforms Histograms Semantics Kernel

来源：评论

学校读者我要写书评

暂无评论

Pulsar Candidate Selection by Assembling Positive Sample Emphasized Classifiers

Pulsar Candidate Selection by Assembling Positive Sample Emp...

引用

International Conference on Computational Intelligence and Security

作者： Yao Yao Xin Xin Ping Guo School of Computer Science and Technology Beijing Institute of Technology Beijing China Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China

ISBN: (纸本)9781509048410

Pulsar candidate selection identifies prospective observations of modern radio pulsar surveys for further inspection in search of real pulsars. Typically, human experts visually select valuable candidates and eliminate radio frequency interference or other noises. Recently, machine learning methods are adopted to automate this task, which saves human labor and makes it possible for processing millions of observations efficiently. Considering the number of positive training samples are relatively too small and the cost of incorrectly labeling a real pulsar candidate as negative is large, we propose a novel hierarchical candidate-sifting model by emphasizing the cost of incorrect prediction of positive samples and assembling multiple classifiers trained with different weighting parameters. Experiments on three pulsar selection datasets demonstrate our proposed method improves the pulsar-sifting performance a lot according to several standard evaluation metrics.

关键词： Training Support vector machines Predictive models Feature extraction Measurement Labeling Histograms

来源：评论

学校读者我要写书评

暂无评论

Modeling multi-source remote sensing image classifier based on the MDL principle: Experimental studies

Modeling multi-source remote sensing image classifier based ...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Huaiying Xia Rukun Hu Bingxin Xu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

In classification of multi-source remote sensing image, it is usually difficult to obtain higher classification accuracy. In the previous work, the modeling technique for the remote sensing image classification based on the minimum description length (MDL) principle with mixture model is analyzed theoretically. In this work, experimental studies are performed for investigating the modeling technique. With intensive experiments and sophisticated analysis, it is found that the developed modeling technique can build a robust classification system, which can avoid classifier over-fitting training data and make the learning process trade-off between bias and variance. Meanwhile, designed mixture model is more efficient to represent real multi-source remote sensing images compared to single model.

关键词：

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14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：