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

43 篇 会议

馆藏范围

43 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

42 篇 工学
- 37 篇 计算机科学与技术...
- 9 篇 电气工程
- 4 篇 控制科学与工程
- 4 篇 测绘科学与技术
- 3 篇 信息与通信工程
- 3 篇 软件工程
- 2 篇 仪器科学与技术
- 2 篇 材料科学与工程（可...
- 2 篇 电子科学与技术（可...
- 1 篇 光学工程
- 1 篇 化学工程与技术
- 1 篇 航空宇航科学与技...
- 1 篇 生物医学工程（可授...
37 篇 理学
- 37 篇 物理学
- 2 篇 数学
- 1 篇 化学
13 篇 医学
- 13 篇 临床医学

主题

21 篇 pattern recognit...
4 篇 automatic target...
3 篇 image processing
3 篇 correlation
2 篇 fuzzy logic
2 篇 image segmentati...
2 篇 texture analysis
2 篇 neural networks
2 篇 machine vision
2 篇 optimal filters
2 篇 robots
2 篇 computer vision ...
2 篇 robot vision
2 篇 computer program...
2 篇 feature extracti...
2 篇 remote sensing
2 篇 optical pattern ...
2 篇 correlators
2 篇 spatial light mo...
2 篇 image classifica...

机构

3 篇 usaf res lab snh...
2 篇 caltech jet prop...
1 篇 lockheed martin ...
1 篇 carnegie mellon ...
1 篇 no telecom netwo...
1 篇 oak ridge natl l...
1 篇 univ cambridge d...
1 篇 nanyang technol ...
1 篇 def r&d canada a...
1 篇 inst super elect...
1 篇 univ burgundy la...
1 篇 univ louisville ...
1 篇 univ bradford de...
1 篇 beijing univ pos...
1 篇 univ arizona dep...
1 篇 tno nl-3769 de s...
1 篇 joanneum res a-8...
1 篇 univ sussex sch ...
1 篇 natl secur res i...
1 篇 northwestern pol...

作者

3 篇 khoury j
3 篇 gianino pd
3 篇 woods cl
2 篇 juday rd
2 篇 reyes g
2 篇 chao th
2 篇 dougherty er
2 篇 monroe se
2 篇 rollins jm
2 篇 zhou hy
1 篇 trimble l
1 篇 liew yb
1 篇 allgair j
1 篇 zou xuechao
1 篇 gmitro af
1 篇 lee sh
1 篇 kadkhoda p.
1 篇 zhao tian
1 篇 liu y
1 篇 prundaru m

语言

43 篇 英文

检索条件"任意字段=Conference on Optical Pattern Recognition XII"

共 43 条记录，以下是1-10 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：

GOP: A Group Object Perception Framework for optical Remote Sensing 7th

GOP: A Group Object Perception Framework for Optical Remote ...

引用

7th Chinese conference on pattern recognition and Computer Vision

作者： Zhang, Hongwei Jin, Lei Zou, Xuechao Zhao, Tian Xing, Junliang Beijing Univ Posts & Telecommun Beijing Peoples R China Beijing Jiaotong Univ Beijing Peoples R China China Telecom EVOL Lab Inst AI TeleAT Beijing Peoples R China Northwestern Polytech Univ China Sch Artificial Intelligence Opt & Elect iOP Xian Peoples R China Tsinghua Univ Beijing Peoples R China

ISBN: (纸本)9789819788576;9789819788583

Objects with close distance in optical remote sensing images often exhibit correlation, such as cars, and ships. However, existing methods generally tackle the perception of objects in optical remote sensing independently. To this end, we propose a Group Object Perception framework (GOP), which utilizes the correlation between objects within the group to improve the perception precision. As a perception framework, GOP is comprehensive including category, bounding box, and mask information. Firstly, we define the group object mainly considering spatial proximity and design an automated labeling scheme to produce labels for GOP. Then we propose a baseline model to detect and segment group objects and sub-objects simultaneously. Furthermore, to utilize the correlation between objects in the group, we propose position supervisor predicting offsets from individual objects to the corresponding group object, which can enhance the detection performance. Additionally, we introduce group category learner to cluster feature similarity from the same class within the group object, further improving the segmentation results. In experiments, GOP obtains 78.2 mAP and 75.9 mAP in rotated object detection and object segmentation on DOTA-v1.0 dataset, respectively. We will release our source codes, pre-trained models, and online demos to facilitate further studies.

关键词： Remote Sensing Object Perception Group Object

来源：评论

学校读者我要写书评

暂无评论

pattern and form recognition of statistically distributed defects on functional optical surfaces

Pattern and form recognition of statistically distributed de...

引用

conference on Videometrics, Range Imaging, and Applications xii;and Automated Visual Inspection

作者： Kadkhoda, P. Chubak, P. Lassahn, M. Ristau, D. Laser Zentrum Hannover eV Germany Hannover Germany Hannover Univ Appl Sci & Arts Hannover Germany

ISBN: (纸本)9780819496072

The inspection of the surface quality of optical components is an essential characterization method for high power laser applications. We report about two different mapping methods based on the measurement of Total Scattering (TS) and phase contrast microscopy. The mappings are used for the determination of the defect density distribution of optical flat surfaces. The mathematical procedure relating data points to a defect area and to the form of objects will be illustrated in details. The involved differential operators and the optimized sub routines adapted to a large number of defects will be underlined. For the decision about the form of the objects, a parameter set including the "fill factor", "edge ratio" and the "polar distance" will be discussed in respect to their versatility range for the basic forms. The calculated distribution will be expressed in terms of affine probability compared to the basic forms. The extracted size and form distribution function of the defects will be presented for selected high reflective and anti-reflective coating samples.

关键词： total scattering phase contrast microscopy labeling polar distance pattern recognition and defect density distribution

来源：评论

学校读者我要写书评

暂无评论

Automated texture-based identification of ovarian cancer in confocal microendoscope images

Automated texture-based identification of ovarian cancer in ...

引用

conference on 3-Dimensional and Multidimensional Microscopy - Image Acquisition and Processing xii

作者： Srivastava, S Rodríguez, JJ Rouse, AR Brewer, MA Gmitro, AF Univ Arizona Dept Elect & Comp Engn Tucson AZ 85721 USA

ISBN: (纸本)0819456756

The fluorescence confocal microendoscope provides high-resolution, in-vivo imaging of cellular pathology during optical biopsy. There are indications that the examination of human ovaries with this instrument has diagnostic implications for the early detection of ovarian cancer. The purpose of this study was to develop a computer-aided system to facilitate the identification of ovarian cancer from digital images captured with the confocal microendoscope system. To achieve this goal, we modeled the cellular-level structure present in these images as texture and extracted features based on first-order statistics, spatial gray-level dependence matrices, and spatial-frequency content. Selection of the best features for classification was performed using traditional feature selection techniques including stepwise discriminant analysis, forward sequential search, a non-parametric method, principal component analysis, and a heuristic technique that combines the results of these methods. The best set of features selected was used for classification, and performance of various machine classifiers was compared by analyzing the areas under their receiver operating characteristic curves. The results show that it is possible to automatically identify patients with ovarian cancer based on texture features extracted from confocal microendoscope images and that the machine performance is superior to that of the human observer.

关键词： confocal microendoscope texture analysis ovarian cancer pattern recognition automated classification

来源：评论

学校读者我要写书评

暂无评论

A self-learning camera for the validation of highly variable and pseudo-random patterns

A self-learning camera for the validation of highly variable...

引用

conference on Machine Vision Applications in Industrial Inspection xii

作者： Kelley, M JAI PULNiX Inc Sunnyvale CA 94089 USA

ISBN: (纸本)0819452068

Reliable and productive manufacturing operations have depended on people to quickly detect and solve problems whenever they appear. Over the last 20 years, more and more manufacturing operations have embraced machine vision systems to increase productivity, reliability and cost-effectiveness, including reducing the number of human operators required. Although machine vision technology has long been capable of solving simple problems, it has still not been broadly implemented. The reason is that until now, no machine vision system has been designed to meet the unique demands of complicated pattern recognition. The ZiCAM(TM) family was specifically developed to be the first practical hardware to meet these needs. To be able to address non-traditional applications, the machine vision industry must include smart camera technology that meets its users' demands for lower costs, better performance and the ability to address applications of irregular lighting, patterns and color. The next-generation smart cameras will need to evolve as a fundamentally different kind of sensor, with new technology that behaves like a human but performs like a computer. Neural network based systems, coupled with self-taught, n-space, non-linear modeling, promises to be the enabler of that next generation of machine vision equipment. Image processing technology is now available that enables a system to match an operator's subjectivity. A Zero-Instruction-Set-Computer (ZISC) powered smart camera allows high-speed fuzzy-logic processing, without the need for computer programming. This can address applications of validating highly variable and pseudo-random patterns. A hardware-based implementation of a neural network, Zero-Instruction-Set-Computer, enables a vision system to "think" and "inspect" like a human, with the speed and reliability of a machine.

关键词： neural network smart camera ZISC pattern recognition ZiCAM image processing vision system

来源：评论

学校读者我要写书评

暂无评论

Deriving dimensionless features for color object recognition in different color models

Deriving dimensionless features for color object recognition...

引用

conference on Signal Processing, Sensor Fusion, and Target recognition xii

作者： Melan, A Rudolph, S Univ Stuttgart Inst Stat & Dynam Aerosp Struct D-70569 Stuttgart Germany

ISBN: (纸本)0819449563

pattern recognition is an important aspect of image processing. Image features are computed from image objects and subsequently used by an object classifier to map (and therefore classify) image objects into their corresponding object classes. To avoid misclassification the image features used should be selected in such a way that they represent the image object similarity appropriately. Similarity however is a well known theoretical concept in physics, where similar phenomena are mathematically expressed as constant dimensionless numbers. These dimensionless numbers are determined from the dimensional representation of the relevant variables by means of a technique called dimensional analysis. In consequence, the concept of dimensional analysis is applied to the derivation of dimensionless features of color images based on various color models. The properties such as color constancy of the resulting dimensionless numbers are studied using analytical and numerical examples. Also the resulting similarity from the different color models is analyzed and discussed.

关键词： pattern recognition color constancy object features similarity dimensional analysis

来源：评论

学校读者我要写书评

暂无评论

Texture-based discrimination of man-made and natural objects in sidescan sonar imagery

Texture-based discrimination of man-made and natural objects...

引用

conference on Signal Processing, Sensor Fusion, and Target recognition xii

作者： Kessel, RT Def R&D Canada Atlantic Dartmouth NS B2Y 3Z7 Canada

ISBN: (纸本)0819449563

High-resolution sidescan sonars are often used in underwater warfare for large-area surveys of the seafloor in the search for sea mines. Much effort has gone toward the automatic detection of sea mines. In its more advanced forms, such auto-detection entails pattern recognition: the automatic assignment of class labels (target/non-target) to signatures according to their distinctive features. This paper demonstrates a texture-based tool for automatically discriminating between man-made and natural objects. Real sonar data is used, and the demonstration includes performance estimates in the form of the receiver-operator characteristic (ROC) curves necessary (though often omitted) for evaluating detectors for operational use. The merits of redefining the allowable automatic responses-from the classes of mine targets ultimately sought, to the class of man-made objects more generally-are reviewed from both the pattern-recognition and operational perspectives.

关键词： sidescan sonar automatic target detection pattern recognition texture analysis mine hunting

来源：评论

学校读者我要写书评

暂无评论

A digital fast pattern recognizer for autonomous target recognition and tracking for advanced missile guidance and UAV reconnaissance

A digital fast pattern recognizer for autonomous target reco...

引用

conference on Signal Processing, Sensor Fusion, and Target recognition xii

作者： Hastbacka, AA Sanders Design Int Inc Wilton NH 03086 USA

ISBN: (纸本)0819449563

A digital Fast pattern Processor (DFPP) system under development for the Naval Air Warfare Center, is funded under a SBIR, Phase III contract. It is an automatic target recognizer and tracker candidate for supersonic missile guidance and unmanned air vehicle (UAV) reconnaissance to meet the U.S. navy's time-critical strike objectives. The former application requires rapid processing of moderate size, real time image arrays, versus large real time image arrays for the latter case. ne DFPP correlates operator selected target filters against observed imagery at 1500 correlations per second as currently implemented with programmable logic devices (PLD's)-equivalent to thirty Pentium III (1 GHz) PC's. High performance and low weight, power, size, and cost of the current version make it ideal for on-board image data processing in UAV's and cruise missiles or for ground station processing. Conversion to application specific integrated circuit (ASIC) technology provides scalable performance to meet future ATR/ATT needs. The Sanders proprietary DFPP technology embodies a Power-FFT, which is the fastest digital fast Fourier transform (DFTT) in the world with performance exceeding supercomputers, at a small fraction of the cost, size, weight, and power. The DFPP operates under control of Sanders Correlation Image Processor (SCIP) program and enables correlation against a plethora of stored target filters (templates).

关键词： UAV reconnaissance digital power FFT autonomous target recognition fast pattern processor correlation processor missile guidance

来源：评论

学校读者我要写书评

暂无评论

New results in the use of polarization diversity in classification of radar targets

New results in the use of polarization diversity in classifi...

引用

12th conference on Automatic Target recognition

作者： Sadjadi, F

ISBN: (纸本)0819444766

The problem of classification of radar targets when both phases and amplitudes are used under diverse angles of polarization ellipse and ellipticity is considered in this paper. Rayleigh quotients and Bhattacharyya distances are derived on synthetic aperture radar target signatures and shown that target separations are on the order of magnitudes larger for this case than traditionally used amplitude only case.

关键词： Automatic Target recognition Bhattacharyya distance pattern classification polarization diversity synthetic aperture radar Rayleigh quotient Fisher discriminant function signal processing

来源：评论

学校读者我要写书评

暂无评论

Implementation of pattern recognition algorithm based on RBF neural network

Implementation of pattern recognition algorithm based on RBF...

引用

conference on Advanced Signal Processing Algorithms, Architectures and Implementations xii

作者： Bouchoux, S Brost, V Yang, F Grapin, JC Paindavoine, M Univ Burgundy Lab LE2I Fac Sci Mirande Aile Ingenieur F-21011 Dijon France

ISBN: (纸本)0819445584

In this paper, we present implementations of a pattern recognition algorithm which uses a RBF (Radial Basis Function) neural network. Our aim is to elaborate a quite efficient system which realizes real time faces tracking and identity verification in natural video sequences. Hardware implementations have been realized on an embedded system developed by our laboratory. This system is based on a DSP (Digital Signal Processor) TMS320C6x. The optimization of implementations allow us to obtain a processing speed of 4.8 images (240 x 320 pixels) per second with a correct rate of 95% of faces tracking and identity verification.

关键词： RBF neural network face tracking and identity verification DSP TMS320C6x real-time image processing embedded system

来源：评论

学校读者我要写书评

暂无评论

Adaptive classification for image segmentation and target recognition

Adaptive classification for image segmentation and target re...

引用

12th conference on Automatic Target recognition

作者： Bargel, B Bers, KH Jäger, K Schwan, G FGAN FOM Forschungsinst Optron & Mustererkennug Res Inst Optron & Pattern Recognit D-76275 Ettlingen Germany

ISBN: (纸本)0819444766

This paper on adaptive image segmentation and classification describes research activities on statistical pattern recognition in combination with methods of object recognition by geometric matching of model and image structures. In addition, aspects of sensor fusion for airborne application systems like terminal missile guidance were considered using image sequences of multispectral data from real sensor systems and from computer simulations. The main aspect of the adaptive classification is the support of model-based structural image analysis by detection of image segments representing specific objects, e.g. forests, rivers and urban areas. The classifier, based on textural features, is automatically adapted to the changes of textural signatures during target approach by interpretation of the segmentation results of each actual frame of the image sequence.

关键词： autonomous systems pattern recognition model based structural analysis image segmentation texture elements feature space partitioning presetting and initialization adaptive classification screening regions of interest image compression

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5页 << < 1 2 3 4 5 > >>

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：