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

662 篇 会议
23 册 图书
22 篇 期刊文献

馆藏范围

707 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

500 篇 工学
- 332 篇 计算机科学与技术...
- 161 篇 软件工程
- 96 篇 测绘科学与技术
- 93 篇 电气工程
- 88 篇 信息与通信工程
- 71 篇 光学工程
- 52 篇 控制科学与工程
- 28 篇 建筑学
- 28 篇 土木工程
- 27 篇 化学工程与技术
- 27 篇 航空宇航科学与技...
- 26 篇 机械工程
- 23 篇 仪器科学与技术
- 22 篇 生物工程
- 21 篇 电子科学与技术（可...
- 19 篇 生物医学工程（可授...
- 15 篇 环境科学与工程（可...
- 12 篇 交通运输工程
- 12 篇 农业工程
225 篇 理学
- 128 篇 物理学
- 83 篇 数学
- 26 篇 化学
- 26 篇 统计学（可授理学、...
- 24 篇 生物学
- 10 篇 地理学
- 10 篇 地球物理学
127 篇 医学
- 125 篇 临床医学
60 篇 管理学
- 43 篇 图书情报与档案管...
- 20 篇 管理科学与工程(可...
15 篇 农学
- 13 篇 作物学
6 篇 军事学
6 篇 艺术学
3 篇 经济学
2 篇 法学
1 篇 教育学
1 篇 文学

主题

194 篇 remote sensing
105 篇 pattern recognit...
78 篇 image processing
37 篇 image segmentati...
31 篇 feature extracti...
25 篇 artificial intel...
25 篇 satellites
19 篇 object detection
19 篇 machine learning
18 篇 training
17 篇 image fusion
17 篇 data mining
17 篇 image analysis
16 篇 image classifica...
16 篇 computer vision
16 篇 image resolution
14 篇 image edge detec...
14 篇 robustness
13 篇 deep learning
13 篇 remote sensing i...

机构

6 篇 tsinghua univers...
6 篇 image processing...
5 篇 university of te...
5 篇 indian institute...
5 篇 dalian universit...
5 篇 university of sy...
5 篇 institute of aut...
5 篇 institute of aut...
5 篇 shenzhen univers...
5 篇 college of infor...
4 篇 institute of ima...
4 篇 sun yat-sen univ...
4 篇 hong kong baptis...
4 篇 southern univers...
3 篇 univ arizona col...
3 篇 mks imaging tech...
3 篇 university of el...
3 篇 peking univ inst...
3 篇 indian institute...
3 篇 national laborat...

作者

8 篇 anon
8 篇 chunhong pan
7 篇 ping guo
5 篇 zhaoxiang zhang
5 篇 hui huang
5 篇 balasubramanian ...
5 篇 jing dong
5 篇 tieniu tan
5 篇 jiwen lu
5 篇 risheng liu
5 篇 wanli ouyang
5 篇 min xu
5 篇 huchuan lu
4 篇 qian yin
4 篇 junwei han
4 篇 jianhuang lai
4 篇 pan chunhong
4 篇 zhang jie
4 篇 yike guo
4 篇 jianguo zhang

语言

688 篇 英文
15 篇 其他
4 篇 中文

检索条件"任意字段=Conference on Image Processing and Pattern Recognition in Remote Sensing II"

共 707 条记录，以下是461-470 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：

18th International conference on pattern recognition - Title

18th International Conference on Pattern Recognition - Title

引用

International conference on pattern recognition

The following topics are discussed: computer vision and image analysis; face and human analysis; face recognition; character recognition and document analysis; clustering algorithms; signal, speech and image processing; signal coding and compression; document image enhancement; visualization and restoration; systems, robotics and applications; biometrics; biomedical imaging; fingerprints; range imaging and remote sensing applications; cognitive approaches and soft computing; gesture and emotion recognition; human computer interaction; semantic analysis for content retrieval; pattern and shape analysis; stereo and motion; learning algorithms; visual pattern recognition; image and data representation; image registration; object detection and recognition; pattern matching; pattern classification; gait, body pose and writer recognition; medical image processing; super-resolution; multimodal recognition; texture analysis; image segmentation; illumination and feature analysis; finger, palm and iris recognition; information retrieval; kernel methods; smart sensors; and surveillance

关键词：

来源：评论

学校读者我要写书评

暂无评论

Automatic extraction of tree crowns from aerial imagery in urban environment

Automatic extraction of tree crowns from aerial imagery in u...

引用

14th International conference on Geoinformatics

作者： Liu, Jiahang Li, Deren Qin, Xunwen Yang, Jianfeng JT Univ Inst Image Proc & Pattern Recognit Shanghai 200240 Peoples R China Chinese Acad Sci Inst Opt & Precis Machines Xian 710068 Peoples R China Wuhan Univ LIESMARS Wuhan 430079 Peoples R China China Geol Survey Beijing 100083 Peoples R China

ISBN: (纸本)9780819465283

Traditionally, field-based investigation is the main method to investigate greenbelt in urban environment, which is costly and low updating frequency. In higher resolution image, the imagery structure and texture of tree canopy has great similarity in statistics despite the great difference in configurations of tree canopy, and their surface structures and textures of tree crown are very different from the other types. In this paper, we present an automatic method to detect tree crowns using high resolution image in urban environment without any apriori knowledge. Our method catches unique structure and texture of tree crown surface, use variance and mathematical expectation of defined image window to position the candidate canopy blocks coarsely, then analysis their inner structure and texture to refine these candidate blocks. The possible spans of all the feature parameters used in our method automatically generate from the small number of samples, and HOLE and its distribution as an important characteristics are introduced into refining processing. Also the isotropy of candidate image block and holes' distribution is integrated in our method. After introduction the theory of our method, aerial imageries were used ( with a resolution about 0.3m) to test our method, and the results indicate that our method is an effective approach to automatically detect tree crown in urban environment.

关键词： tree detection image segmentation vegetation extraction image interpretation automatic recognition high resolution imagery

来源：评论

学校读者我要写书评

暂无评论

Commodity cluster and hardware-based massively parallel implementations of hyperspectral imaging algorithms

Commodity cluster and hardware-based massively parallel impl...

引用

conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral imagery Xii

作者： Plaza, Antonio Chang, Chein-, I Plaza, Javier Valencia, David Univ Extremadura Comp Sci Dept Avda Univ S-N E-10071 Caceres Spain Univ Maryland Dept Comp Sci & Elect Engn Remote Sensing Signal & Image Proc Lab Baltimore MD 21250 USA

ISBN: (纸本)0819462896

The incorporation of hyperspectral sensors aboard airborne/satellite platforms is currently producing a nearly continual stream of multidimensional image data, and this high data volume has soon introduced new processing challenges. The price paid for the wealth spatial and spectral information available from hyperspectral sensors is the enormous amounts of data that they generate. Several applications exist, however, where having the desired information calculated quickly enough for practical use is highly desirable. High computing performance of algorithm analysis is particularly important in homeland defense and security applications, in which swift decisions often involve detection of (sub-pixel) military targets (including hostile weaponry, camouflage, concealment, and decoys) or chemical/biological agents. In order to speed-up computational performance of hyperspectral imaging algorithms, this paper develops several fast parallel data processing techniques. Techniques include four classes of algorithms: (1) unsupervised classification, (2) spectral unmixing, and (3) automatic target recognition, and (4) onboard data compression. A massively parallel Beowulf cluster (Thunderhead) at NASA's Goddard Space Flight Center in Maryland is used to measure parallel performance of the proposed algorithms. In order to explore the viability of developing onboard, real-time hyperspectral data compression algorithms, a Xilinx Virtex-ii field programmable gate array (FPGA) is also used in experiments. Our quantitative and comparative assessment of parallel techniques and strategies may help image analysts in selection of parallel hyperspectral algorithms for specific applications.

关键词： hyperspectral imaging parallel computing commodity clusters field programmable gate arrays

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

Digital image processing of High Resolution Aerial Photograph of Shallow Marine Sanctuary, Victoria, Australia

Digital Image Processing of High Resolution Aerial Photograp...

引用

International conference on Advances in Space Technologies, ICAST

作者： Fawad Saeed Water and Power Development Authority (WAPDA)

In this paper the potential of remote sensing as a tool to study marine sanctuary has been explored. There are two main methods that can be used to extract information from the aerial photograph/satellite imagery; visual interpretation and digital image processing. Visual interpretation takes advantage of the human skills to recognize data "content" by combining several elements of image interpretation. It relies on experience, a prior knowledge and skilled analysts qualities to produce excellent results. Alternatively, digital image classification employs computer techniques which are mostly based on the reflection values of individual pixels and use statistical pattern recognition methods. In the current study, the main area of interest was distribution of sand, rocky reef, rocky rubble and sea grass in the sanctuary. The study showed that the supervised classification approach was a superior technique to employ for such studies as compare to other traditional approaches. Here, the higher degree of interaction between the analyst and the machine complements the limitations of each other. Furthermore, the analyst is also given the opportunity to "control" which digital signatures best qualify to represent a certain resource class considering the fact that the analyst has access to ground truth data to fine tune the classification

关键词： Digital images image resolution Australia remote sensing Data mining Satellites Humans image recognition Reflection Pixel

来源：评论

学校读者我要写书评

暂无评论

An Algorithm to Edge Detection Based on SUSAN Filter and Embedded Confidence

An Algorithm to Edge Detection Based on SUSAN Filter and Emb...

引用

International conference on Intelligent Systems Design and Applications (ISDA)

作者： Shenghua Xu Litao Han Lihua Zhang State Key Laboratory of Information Engineering in Surveying mapping and Remote Sensing Wuhan University of China Wuhan China

Edge detection is the base of the image measuring, image segmentation, image compressing and pattern recognition, and so on. The existing edge detection methods are analyzed, and the SUSAN filter and edge detection with embedded confidence are studied respectively. Then a new method based on SUSAN filter and embedded confidence is proposed. This new algorithm combines them to realize respective value. The experimental results show that this algorithm is more robust to noise and is rich in feature content and accurate. The algorithm has terribly capacious developed foreground

关键词： image edge detection Filters Filtering algorithms Detectors Pixel image segmentation image coding image recognition image processing Information filtering

来源：评论

学校读者我要写书评

暂无评论

A Higher-Order Active Contour Model for Tree Detection

A Higher-Order Active Contour Model for Tree Detection

引用

International conference on pattern recognition

作者： P. Horvath I. Jermyn J. Zerubia Z. Kato Ariana joint research group CNRS/INRIA/UNSA INRIA Sophia-Antipolis France Institute of Informatics University of Szeged Szeged Hungary

We present a model of a `gas of circles', the ensemble of regions in the image domain consisting of an unknown number of circles with approximately fixed radius and short range repulsive interactions, and apply it to the extraction of tree crowns from aerial images. The method uses the recently introduced `higher order active contours' (HOACs), which incorporate long-range interactions between contour points, and thereby include prior geometric information without using a template shape. This makes them ideal when looking for multiple instances of an entity in an image. We study an existing HOAC model for networks, and show via a stability calculation that circles stable to perturbations are possible for constrained parameter sets. Combining this prior energy with a data term, we show results on aerial imagery that demonstrate the effectiveness of the method and the need for prior geometric knowledge. The model has many other potential applications

关键词： Active contours Data mining Geometry Forestry Informatics Shape Stability remote sensing image processing Muscles

来源：评论

学校读者我要写书评

暂无评论

Radar Signal Classification Using Pca-Based Features

Radar Signal Classification Using Pca-Based Features

引用

International conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： A.K. Mishra B. Mulgrew IDCOM University of Edinburgh Edinburgh UK

Principal component analysis (PCA) has been used in many applications ranging from social science to space science, for the purpose of data compression and feature extraction. Usage of PCA for synthetic aperture radar (SAR) image classification, though widely reported by remote-sensing researchers, has not been exploited much by automatic target recognition (ATR) community. In the present paper, PCA has been used in SAR-ATR using the MSTAR data base, and comparison has been made with the conventional conditional Gaussian model based Bayesian classifier (M.D. DeVore and J.A. O'Sullivan, 2002). The results have been compared based on percentage of correct classification, receiver operating characteristics (ROC), and performance with limited amount of training data. By all standards of comparison, the PCA based classifier was observed to outperform the conditional Gaussian model based Bayesian classifier (CGBC) or at the worst it performs at par. And given the computational and algorithmic simplicity of PCA based classifier, the new algorithm was concluded to be a highly prospective candidate for real time ATR systems

关键词： pattern classification Principal component analysis Bayesian methods Radar imaging Radar remote sensing Data compression Feature extraction Synthetic aperture radar image classification remote sensing

来源：评论

学校读者我要写书评

暂无评论

Proceedings of SPIE: image processing and pattern recognition in remote sensing ii

Proceedings of SPIE: Image Processing and Pattern Recognitio...

引用

image processing and pattern recognition in remote sensing ii

The proceedings contain 14 papers from the Proceedings of SPIE: image processing and pattern recognition in remote sensing ii. The topics discussed include: exploitation of complementary sensors for precise ground-registration of sensed objects;segmentation of LANDSAT TM image using the Markov random field model toward a category classification of higher accuracy;real-time decision making on EO-1 using onboard science analysis;conflation technology in spatial data integration on the Internet;potential of IKONOS images for updating land-use-based map of China through data fusion and integration;and IEEE1394 and entropy reduction techniques as applied to remote sensing spacecraft communication systems.

关键词： remote sensing

来源：评论

学校读者我要写书评

暂无评论

PROBABILISTIC SIMILARITY MEASURES ANALYSIS FOR remote sensing image RETRIEVAL

PROBABILISTIC SIMILARITY MEASURES ANALYSIS FOR REMOTE SENSIN...

引用

2006 International conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： PING GUO QIAN BAO QIAN YIN Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China

In image database retrieval there are many classical similarity measures that can be used to find the target image, these measures are mostly belong to geometry model from the point of view of the data model, while little attention has been devoted to the studies on methods based on probability density distribution. In this paper we experimental investigate some probabilistic similarity measures, present two methods for design of the similarity function of two mixture Gaussian distributions, on the basis of the nearest neighbor rule and K nearest neighbor rule respectively. An experimental study was conducted to examine and evaluate the measures for application to image databases, and the experiment results show that the methods based on K nearest neighbor rule achieve better performance.

关键词： Probabilistic similarity measures class separability measures mixture Gaussian distribution K nearest neighbor rule image histogram

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71页 << < 43 44 45 46 47 48 49 50 51 52 > >>

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：