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

624 篇 会议
56 篇 期刊文献
9 册 图书
2 篇 学位论文

馆藏范围

691 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

621 篇 工学
- 509 篇 计算机科学与技术...
- 399 篇 控制科学与工程
- 227 篇 软件工程
- 178 篇 光学工程
- 159 篇 电气工程
- 57 篇 机械工程
- 49 篇 电子科学与技术（可...
- 38 篇 信息与通信工程
- 36 篇 仪器科学与技术
- 30 篇 材料科学与工程（可...
- 22 篇 交通运输工程
- 11 篇 测绘科学与技术
- 9 篇 航空宇航科学与技...
- 9 篇 生物工程
- 8 篇 建筑学
- 7 篇 力学（可授工学、理...
- 7 篇 土木工程
- 7 篇 安全科学与工程
- 6 篇 生物医学工程（可授...
437 篇 理学
- 407 篇 物理学
- 123 篇 数学
- 12 篇 统计学（可授理学、...
- 10 篇 生物学
- 4 篇 海洋科学
44 篇 管理学
- 40 篇 管理科学与工程(可...
- 8 篇 工商管理
- 5 篇 图书情报与档案管...
18 篇 医学
- 18 篇 临床医学
5 篇 经济学
- 5 篇 应用经济学
5 篇 教育学
- 5 篇 教育学
5 篇 军事学
3 篇 农学
1 篇 法学
1 篇 艺术学

主题

183 篇 computer vision
99 篇 machine vision
77 篇 robots
72 篇 robot vision
66 篇 computer vision ...
62 篇 mobile robots
50 篇 image processing
46 篇 intelligent robo...
36 篇 image segmentati...
30 篇 cameras
29 篇 robotics
23 篇 object recogniti...
20 篇 sensors
19 篇 navigation
18 篇 visualization
17 篇 stereo vision
17 篇 detection and tr...
16 篇 visual process m...
15 篇 active vision
14 篇 fuzzy logic

机构

21 篇 univ cincinnati ...
8 篇 univ of cincinna...
6 篇 univ detroit mer...
5 篇 mansoura univ. e...
5 篇 univ. of cincinn...
4 篇 univ. siegen sie...
4 篇 federal armed fo...
4 篇 smart computer v...
4 篇 carnegie mellon ...
3 篇 carnegie mellon ...
3 篇 univ. of surrey ...
3 篇 caltech jet prop...
3 篇 tianjin univ sta...
3 篇 massachusetts in...
3 篇 us army tardec w...
3 篇 univ. of birming...
3 篇 hashemite univ. ...
3 篇 brigham young un...
3 篇 univ. of cincinn...
3 篇 georgia inst of ...

作者

17 篇 hall el
16 篇 hall ernest l.
11 篇 theisen bernard ...
9 篇 lauinger n
8 篇 lee dah-jye
8 篇 roning juha
8 篇 hall e
7 篇 paulik mark
7 篇 krishnan mohan
6 篇 feng weijia
6 篇 lyons damian m.
6 篇 casasent david p...
5 篇 schenker ps
5 篇 liao xq
5 篇 luo chaomin
5 篇 el-konyaly el-sa...
5 篇 ghaffari m.
5 篇 dickerson stephe...
5 篇 zhang baofeng
5 篇 liao x.

语言

682 篇 英文
8 篇 中文
1 篇 其他

检索条件"任意字段=Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques"

共 691 条记录，以下是251-260 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：

Bayesian stereo: 3D vision designed for sensor fusion

Bayesian stereo: 3D vision designed for sensor fusion

引用

Conference on intelligent robots and computer vision XXII - algorithms, techniques and Active vision

作者： Larson, J Pless, R Washington Univ St Louis MO 63130 USA

ISBN: (纸本)081945561X

Classical stereo algorithms attempt to reconstruct 3D models of a scene by matching points between two images. Finding points that match is an important part of this process, and point matches are most commonly chosen as the minimum of an error function based on color or local texture. Here we motivate a probabilistic approach to this point matching problem, and provide an experimental design for the empirical measurement of the color matching error for corresponding points. We use this prior in a Bayesian scene reconstruction example, and show that we get better 3D reconstruction by not committing to a specific pixel match early in the visual processing. This allows a calibrated stereo camera to be considered as a probabilistic volume sensor --- which allows it to be more easily integrated with scene structure measurements from other kinds of sensors.

关键词： stereo Bayesian probabilistic sensor fusion

来源：评论

学校读者我要写书评

暂无评论

The 12^TH annual intelligent ground vehicle competition:: Team approaches to intelligent vehicles

The 12<SUP>TH</SUP> annual intelligent ground vehicle compet...

引用

Conference on intelligent robots and computer vision XXII - algorithms, techniques and Active vision

作者： Theisen, BL Maslach, D USA Tank Automat Res Dev & Engn Ctr Warren MI 48397 USA

ISBN: (纸本)081945561X

The intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics, and mobile platform fundamentals to design and build an unmanned system. Both U.S. and international teams focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 12 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 43 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the three-day competition are highlighted. Finally, an assessment of the competition based on participant feedback is presented.

关键词： intelligent robots autonomous systems ground vehicles engineering education IGVC

来源：评论

学校读者我要写书评

暂无评论

computer vision inspection of rice seeds quality with discriminant analysis

Computer vision inspection of rice seeds quality with discri...

引用

Conference on intelligent robots and computer vision XXII - algorithms, techniques and Active vision

作者： Cheng, F Ying, YB Zhejiang Univ Coll Biosyst Engn & Food Sci Hangzhou 310029 Peoples R China

ISBN: (纸本)081945561X

This study was undertaken to develop computer vision-based rice seeds inspection technology for quality control. Color image classification using a discriminant analysis algorithm identifying germinated rice seed was successfully implemented. The hybrid rice seed cultivars involved were Jinyou402, Shanyou10, Zhongyou207 and Jiayou99. Sixteen morphological features and six color features were extracted from sample images belong to training sets. The color feature of 'Huebmean' shows the strongest classification ability among all the features. Computed as the area of seed region divided by area of the smallest convex polygon that can contain the seed region, the feature of 'Solidity' is prior to the other morphological features in germinated seeds recognition. Combined with the two features of 'Huebmean' and 'Solidity', discriminant analysis was used to classify normal rice seeds and seeds germinated on panicle. Results show that the algorithm achieved an overall average accuracy of 98.4% for both of normal seeds and germinated seeds in all cultivars. The combination of 'Huebmean' and 'Solidity' was proved to be a good indicator for germinated seeds. The simple discriminant algorithm using just two features shows high accuracy and good adaptability.

关键词： computer vision rice seeds germinated discriminant analysis

来源：评论

学校读者我要写书评

暂无评论

Camera localization methods for intelligent room systems using RF techniques

Camera localization methods for intelligent room systems usi...

引用

Intellignt robots and computer vision XXII: algorithms, techniques, and Active vision

作者： Natarajan, Pradeep Mundhenk, T. Nathan Bellman, K. Itti, L. Arbib, M. Computer Science Department Henri Salvatori Comp. Science Center University of Southern California Los Angeles CA 90089-0781 Neuroscience Program Hedco Neuroscience Building University of Southern California Los Angeles CA 90089-2520 Aerospace Integration Science Center Aerospace Corporation 2350 E. El Segundo Blvd. El Segundo CA 90245-4691

One of the important components of a multi sensor "intelligent" room, which can observe, track and react to its occupants, is a multi camera system. This system involves the development of algorithms that enable a set of cameras to communicate and cooperate with each other effectively so that they can monitor the events happening in the room. To achieve this, the cameras typically must first build a map of their relative locations. In this paper, we discuss a novel RF based technique for estimating distances between cameras. The algorithm proposed for RF can estimate distances with relatively good accuracy even in the presence of random noise.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Citrus fruit recognition using color image analysis

Citrus fruit recognition using color image analysis

引用

Conference on intelligent robots and computer vision XXII - algorithms, techniques and Active vision

作者： Xu, HR Ying, YB Zhejiang Univ Coll Biosyst Engn & Food Sci Hangzhou 310029 Peoples R China

ISBN: (纸本)081945561X

An algorithm for the automatic recognition of citrus fruit on the tree was developed. Citrus fruits have different color with leaves and branches portions. Fifty-three color images with natural citrus-grove scenes were digitized and analyzed for red, green, and blue (RGB) color content. The color characteristics of target surfaces (fruits, leaves, or branches) were extracted using the range of interest (ROI) tool. Several types of contrast color indices were designed and tested. In this study, the fruit image was enhanced using the (R-B) contrast color index because results show that the fruit have the highest color difference among the objects in the image. A dynamic threshold function was derived from this color model and used to distinguish citrus fruit from background. The results show that the algorithm worked well under frontlighting or backlighting condition. However, there are misclassifications when the fruit or the background is under a brighter sunlight.

关键词： machine vision citrus detection color indices dynamic thresholdng image processing

来源：评论

学校读者我要写书评

暂无评论

Surface roughness estimation of shot blasted steel bars using machine vision

Surface roughness estimation of shot blasted steel bars usin...

引用

Conference on intelligent robots and computer vision XXII - algorithms, techniques and Active vision

作者： Lydén, S Kälviäinen, H Nykänen, J Lappeenranta Univ Technol Dept Informat Proc FIN-53851 Lappeenranta Finland Imatra Steel Imatra FIN-55100 Imatra Finland

ISBN: (纸本)081945561X

During the manufacturing process steel bars are cleaned of roll scale by shot blasting, before further processing the bars by drawing. The main goal of this project is to increase the automation of the shot blasting process by machine vision. For this purpose a method is needed for estimating the surface roughness and other anomalies from the steel bars from digital images after the shot blasting. The goal of this method is to estimate if the quality of shot blasting is sufficient considering the quality of the final products after the drawing. In this project a method for normalising the images is considered and several methods for estimating the actual roughness level are experimented. During the experiments a best method was one where the roughness levels are calculated directly from the images as if the images were similar to other measuring sources and the grey-level values in the images represent the deviation on the bar surface. This at least separates the different samples.

关键词： shot blasting steel bars surface roughness image processing machine vision differential evolution

来源：评论

学校读者我要写书评

暂无评论

Circle detection algorithm for counting canes in a bundle

Circle detection algorithm for counting canes in a bundle

引用

Intellignt robots and computer vision XXII: algorithms, techniques, and Active vision

作者： Yeong, WaiKai Batchelor, Bruce G. School of Computer Science Cardiff University 5 The Parade Cardiff CF24 3XF United Kingdom

A circle detection technique and its application in counting the number of pieces of canes in a bundle are described. Pre-processing is performed on the "raw" image from the camera, to obtain a binary image that is suitable for counting. Blobs in this image are then isolated in turn and each one is analysed to extract properties of interest, including left, right, top and bottom limits of the blobs, their centroid positions, sizes, and perimeters. These measurements are further analysed, so that objects that are approximately circular can be identified. In practice, factors such as lighting, the grade of cane and physical state of the cut ends may result in degraded circular objects being present in this binary image. Possible processes for identifying "circular" objects from a fragmented image are reviewed and a novel technique is proposed.

关键词： algorithms

来源：评论

学校读者我要写书评

暂无评论

A method for integrating vision and laser range measurements in autonomous ground robotic vehicles

A method for integrating vision and laser range measurements...

引用

Conference on intelligent robots and computer vision XXII - algorithms, techniques and Active vision

作者： Riggins, RN Mutter, BV Bluefield State Coll Bluefield WV USA

ISBN: (纸本)081945561X

This paper presents a method to integrate non-stereoscopic vision information with laser distance measurements for Autonomous Ground Robotic Vehicles (AGRV). The method assumes a horizontally-mounted Laser Measurement System (LMS) sweeping 180 degrees in front from right to left every one second, and a video camera mounted five feet high pointing to the front and down at 45 degrees to the horizontal. The LMS gives highly accurate obstacle position measurements in a two-dimensional plane whereas the vision system gives limited and not-so-accurate information on obstacle positions in three dimensions. The vision system can also see contrasts between ground markings. Many AGRVs have similar sensors in similar arrangements. The method presented here is general enough for many types of distance measurements and cameras and lenses. Since the data from these two sensors are in radically different formats, AGRVs need a scheme to combine this data into a common format so that the data can be compared and correlated. Having a successful integration method allows the AGRV to make smart path-finding navigation decisions. Integrating these two sensors is one of the challenges for AGRVs that use this approach. The method presented in this paper employs a geometrical approach to combine the two data sets in real time. Tests, accomplished in simulation as well as on an actual AGRV, show excellent results.

关键词： Sensor Integration Autonomous Ground Robotic Vehicles vision Laser Measurement System

来源：评论

学校读者我要写书评

暂无评论

techniques for evaluating optical flow for visual odometry in extreme terrain

Techniques for evaluating optical flow for visual odometry i...

引用

2004 IEEE/RSJ International Conference on intelligent robots and Systems (IROS)

作者： Campbell, Jason Sukthankar, Rahul Nourbakhsh, Illah Intel Research Pittsburgh Pittsburgh PA United States Robotics Institute Pittsburgh PA United States NASA Ames Research Center Moffett Field CA United States

ISBN: (纸本)0780384636

Motion vision (visual odometry, the estimation of camera egomotion) is a well researched field, yet has seen relatively limited use despite strong evidence from biological systems that vision can be extremely valuable for navigation. The limited use of such vision techniques has been attributed to a lack of good algorithms and insufficient computer power, but both of those problems were resolved as long as a decade ago. A gap presently yawns between theory and practice, perhaps due to perceptions of robot vision as less reliable and more complex than other types of sensing. We present an experimental methodology for assessing the real-world precision and reliability of visual odometry techniques in both normal and extreme terrain. This paper evaluates the performance of a mobile robot equipped with a simple vision system in common outdoor and indoor environments, including grass, pavement, ice, and carpet. Our results show that motion vision algorithms can be robust and effective, and suggest a number of directions for further development.

关键词： Robotics

来源：评论

学校读者我要写书评

暂无评论

Teaching the computer subjective notions of feature connectedness in a visual scene for real time vision.

Teaching the computer subjective notions of feature connecte...

引用

Conference on intelligent robots and computer vision XXII - algorithms, techniques and Active vision

作者： Mundhenk, TN Landauer, C Bellman, K Arbib, NA Itti, L Univ So Calif Dept Comp Sci Henry Salvatori Comp Sci Ctr Los Angeles CA 90089 USA

ISBN: (纸本)081945561X

We discus a tool kit for usage in scene understanding where prior information about targets is not necessarily understood. As such, we give it a notion of connectivity such that it can classify features in an image for the purpose of tracking and identification. The tool VFAT (Visual Feature Analysis Tool) is designed to work in real time in an intelligent multi agent room. It is built around a modular design and includes several fast vision processes. The first components discussed are for feature selection using visual saliency and Monte Carlo selection. Then features that have been selected from an image are mixed into useful and more complex features. All the features are then reduced in dimension and contrasted using a combination of Independent Component Analysis and Principle Component Analysis (ICA/PCA). Once this has been done, we classify features using a custom non-parametric classifier (NPclassify) that does not require hard parameters such as class size or number of classes so that VFAT can create classes without stringent priors about class structure. These classes are then generalized using Gaussian regions which allows easier storage of class properties and computation of probability for class matching. To speed up to creation of Gaussian regions we use a system of rotations instead of the traditional Psuedo-inverse method. In addtion to discussing the structure of VFAT we discuss training of the current system which is relatively easy to perform. ICA/PCA is trained by giving VFAT a large number of random images. The ICA/PCA matrix is computed by features extracted by VFAT. The non-parametric classifier NPclasify it trained by presenting it with images of objects having it decide how many objects it thinks it sees. The difference between what it sees and what it is supposed to see in terms of the number of objects is used as the error term and allows VFAT to learn to classify based upon the experimenters subjective idea of good classification.

关键词： iRoom biological vision tool multi agent saliency real time

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70页 << < 22 23 24 25 26 27 28 29 30 31 > >>

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：