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

178 篇 会议
55 篇 期刊文献

馆藏范围

233 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

101 篇 工学
- 63 篇 计算机科学与技术...
- 52 篇 软件工程
- 20 篇 光学工程
- 18 篇 控制科学与工程
- 16 篇 机械工程
- 13 篇 电气工程
- 13 篇 信息与通信工程
- 11 篇 生物医学工程（可授...
- 10 篇 生物工程
- 9 篇 交通运输工程
- 7 篇 安全科学与工程
- 6 篇 仪器科学与技术
- 6 篇 电子科学与技术（可...
- 5 篇 土木工程
- 3 篇 力学（可授工学、理...
- 3 篇 化学工程与技术
47 篇 理学
- 24 篇 物理学
- 23 篇 数学
- 12 篇 统计学（可授理学、...
- 11 篇 生物学
- 5 篇 系统科学
- 4 篇 化学
- 3 篇 海洋科学
17 篇 管理学
- 13 篇 管理科学与工程(可...
- 7 篇 工商管理
- 7 篇 图书情报与档案管...
8 篇 医学
- 8 篇 临床医学
- 6 篇 基础医学(可授医学...
- 4 篇 药学(可授医学、理...
2 篇 法学
- 2 篇 社会学
1 篇 哲学
1 篇 教育学
1 篇 文学
1 篇 农学
1 篇 艺术学

主题

75 篇 computer vision
48 篇 robot vision sys...
41 篇 cameras
35 篇 laboratories
26 篇 layout
21 篇 intelligent robo...
20 篇 humans
19 篇 robot sensing sy...
17 篇 vehicle detectio...
17 篇 robustness
16 篇 intelligent vehi...
15 篇 vehicle driving
13 篇 feature extracti...
12 篇 visualization
12 篇 image analysis
12 篇 vehicles
11 篇 computational mo...
10 篇 object detection
10 篇 detectors
9 篇 sensor systems

机构

28 篇 computer vision ...
16 篇 computer vision ...
12 篇 computer vision ...
10 篇 computer vision ...
7 篇 computer vision ...
5 篇 computer vision ...
5 篇 department of qu...
5 篇 ihu strasbourg s...
5 篇 computer vision ...
5 篇 heidelberg
4 篇 centre for medic...
4 篇 computer vision ...
4 篇 department of me...
4 篇 faculty of mathe...
4 篇 department of ge...
3 篇 department of co...
3 篇 university of pe...
3 篇 department of co...
3 篇 vector institute...
3 篇 erlangen-nürnber...

作者

56 篇 m.m. trivedi
20 篇 mohan m. trivedi
17 篇 trivedi mohan m.
10 篇 j.c. mccall
8 篇 m. trivedi
8 篇 mohan trivedi
7 篇 trivedi mohan
7 篇 trivedi mm
6 篇 panos trahanias
6 篇 s.b. marapane
6 篇 t. gandhi
6 篇 brendan morris
5 篇 michail maniadak...
5 篇 bakas spyridon
5 篇 gandhi tarak
5 篇 g. ravichandran
5 篇 eshed ohn-bar
5 篇 reyes mauricio
5 篇 menze bjoern
5 篇 in so kweon

语言

224 篇 英文
8 篇 其他
1 篇 中文

检索条件"机构=The Computer Vision And Robotics Research Laboratory"

共 233 条记录，以下是61-70 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：

Learning multi-lane trajectories using vehicle-based vision

Learning multi-lane trajectories using vehicle-based vision

引用

International Conference on computer vision Workshops (ICCV Workshops)

作者： Sayanan Sivaraman Brendan Morris Mohan Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego USA

Safe operation of a motor vehicle requires awareness of the current traffic situation as well as the ability to predict future maneuvers. In order to provide an intelligent vehicle the ability to make predictions, this work proposes a framework for understanding the driving situation based on vehicle mounted vision sensors. Vehicles are tracked using Kalman filtering based on a vision-based system that detects and tracks using a combination of monocular and stereo-vision. The vehicles' full trajectories are recorded, and a data-driven learning framework has been applied to automatically learn surround behaviors. By learning based on observations, the ADAS system is being trained by experience. Learned trajectories have been compared between dense and free-flowing traffic conditions. Preliminary experimental results using real-world multi-lane highways show the basic promise of this approach. Future research directions are discussed.

关键词： Vehicles Trajectory Hidden Markov models Mathematical model Detectors Equations Training

来源：评论

学校读者我要写书评

暂无评论

Lidar based off-road negative obstacle detection and analysis

Lidar based off-road negative obstacle detection and analysi...

引用

International Conference on Intelligent Transportation

作者： Jacoby Larson Mohan Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

In order for an autonomous unmanned ground vehicle (UGV) to drive in off-road terrain at high speeds, it must analyze and understand its surrounding terrain in realtime: it must know where it intends to go, where are the hazards, and many details of the topography of the terrain. Much research has been done in the way of obstacle avoidance, terrain classification, and path planning, but still so few UGV systems can accurately traverse off-road environments at high speeds autonomously. One of the most dangerous hazards found off-road are negative obstacles, mainly because they are so difficult to detect. We present algorithms that analyze the terrain using a point cloud produced by a 3D laser range finder, then attempt to classify the negative obstacles using both a geometry-based method we call the Negative Obstacle DetectoR (NODR) as well as a support vector machine (SVM) algorithm. The terrain is analyzed with respect to a large UGV with the sensor mounted up high as well as a small UGV with the sensor mounted low to the ground.

关键词： Laser radar Vehicles Support vector machines Robot sensing systems Lasers Three dimensional displays Equations

来源：评论

学校读者我要写书评

暂无评论

Retinal vessel tortuosity evaluation via Circular Hough Transform

Retinal vessel tortuosity evaluation via Circular Hough Tran...

引用

Iranian Conference of Biomedical Engineering (ICBME)

作者： Farnoosh Ghadiri HamidReza Pourreza Touka Banaee Morteza Delgir Computer Engineering Department Machine Vision Laboratory Ferdowsi University of Mashhad Iran Computer Engineering Department Machine Vision Laboratory University of Ferdowsi Mashhad Iran Ophthalmic Research Center Khatam-Al-Anbia Hospital Medical science University of Mashhad Iran Computer Science Department Robotics Laboratory Northeastern University USA

Retinal vessel tortuosity has shown to be significantly associated with cardiovascular diseases such as hypertension and diabetes. Despite importance of this field a few techniques have been proposed yet. All previous methods rely on a vessel extraction phase, which its accuracy affects final output and also time consuming. Nobility of presented algorithm is to introduce a method for evaluating retinal vessel tortuosity without any explicit vessel detection. We use the Circular Hough Transform (CHT) based on gradient field of the retinal image. Each vessel curve is detected as a semi-circle by Hough transform and tortuosity of the curve is determined with the help of accumulated value of circle center and its radius. As there are no any specific database for tortuosity evaluation, the algorithm was tasted on database consisting of 40 images, mixture of DRIVE database and images from Khatam-Al-Anbia Hospital consisting of 40 retinal images, of which 20 were tortuous and 20 were non-tortuous. The proposed algorithm can achieve classification rate of 92% along with less computation time in compare of previous methods.

关键词： Transforms Retinal vessels Classification algorithms Biomedical measurements Biomedical imaging Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Contextual activity visualization from long-term video observations

Contextual activity visualization from long-term video obser...

引用

作者： Morris, Brendan Tran Trivedi, Mohan Manubhai Computer Vision and Robotics Research Laboratory University of California San Diego United States

The Contextual Activity Notification Visualization Analysis System (Canvas) provides a user interaction interface for instantaneous feedback of contextual processing units that enable high-level semantic extraction an... 详细信息

关键词： Visualization

来源：评论

学校读者我要写书评

暂无评论

Improving stereo camera depth measurements and benefiting from intermediate results

Improving stereo camera depth measurements and benefiting fr...

引用

IEEE Symposium on Intelligent Vehicle

作者： C. Høilund T. B. Moeslund C. B. Madsen M. M. Trivedi Laboratory of Computer Vision and Media Technology Aalborg University Denmark Computer Vision and Robotics Research Laboratory University of California San Diego USA

This paper presents a method for improving the disparity values obtained with a stereo camera by applying an iconic Kalman filter and known ego-motion. The improvements are demonstrated in an application of determining the free space in a scene as viewed by a vehicle-mounted camera. Using disparity maps from a stereo camera and known camera motion, the disparity maps are first filtered by an iconic Kalman filter, operating on each pixel individually, thereby reducing variance and increasing the density of the filtered disparity map. Then, a stochastic occupancy grid is calculated from the filtered disparity map, providing a top-down view of the scene where the uncertainty of disparity measurements are taken into account. These occupancy grids are segmented to indicate a maximum depth free of obstacles, enabling the marking of free space in the accompanying intensity image. Even without motion of the camera, the quality of the disparity map is increased significantly. Applications of the intermediate results are discussed, enabling features such as motion detection and quantifying the certainty of the measurements. The evaluation shows significant improvement in disparity variance and disparity map density, and consequently an improvement in the application of marking free space.

关键词： Filters Stereo vision Intelligent vehicles Robot vision systems Layout USA Councils Smart cameras Laboratories computer vision Motion detection

来源：评论

学校读者我要写书评

暂无评论

Vehicle Iconic Surround Observer: Visualization platform for intelligent driver support applications

Vehicle Iconic Surround Observer: Visualization platform for...

引用

IEEE Symposium on Intelligent Vehicle

作者： Brendan Morris Mohan Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego La Jolla CA USA

With the introduction of intelligent driver support systems, vehicles have become more comfortable and safer. But, these systems require new sensors and the information they contain must be efficiently presented to the driver. The cognitive demands for interpreting these signals may prove to be a distraction with negative impact on driving performance. This work describes a unified visualization scheme, the Vehicle Iconic Surround Observer, capable of introducing new surround sensors into a common display environment which quickly conveys critical surround context with minimal driver interpretation.

关键词： Vehicle driving Visualization Intelligent vehicles Intelligent sensors Vehicle safety Mechanical sensors Lenses Intelligent robots Laboratories Intelligent systems

来源：评论

学校读者我要写书评

暂无评论

Self-organized executive control functions

Self-organized executive control functions

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Michail Maniadakis Panos Trahanias Jun Tani Computational Vision and Robotics Laboratory Institute of Computer Science Foundation for Research and Technology Hellas Crete Greece Laboratory for Behavior and Dynamic Cognition RIKEN Brain Science Institute Wako Saitama Japan

Executive control incorporates cognitive functions involved in the control and management of other cognitive processes. Such high-level skills are hard to be explored with brain imaging studies because they require complex and persistent experimental procedures. Alternatively, computational modeling may provide a new way to indirectly explore executive control mechanisms. The current work adopts this latter approach to explore possible characteristics of executive control, focusing particularly on behavioral rule switching and confidence neurodynamics in artificial agents. To this end, our study explores a robotic version of the classical Wisconsin Card Sorting Test, incorporating also the option of betting. Our ability to perform multiple and statistically independent computational experiments together with the in-depth study of the mechanisms created in the artificial cognitive systems, provides suggestions for the executive control aspects of the human brain.

关键词： Switches Robot sensing systems Brain modeling Neurons Encoding

来源：评论

学校读者我要写书评

暂无评论

Unsupervised learning of motion patterns of rear surrounding vehicles

Unsupervised learning of motion patterns of rear surrounding...

引用

2009 IEEE International Conference on Vehicular Electronics and Safety, ICVES 2009

作者： Morris, Brendan Trivedi, Mohan Computer Vision and Robotics Research Laboratory University of California San Diego San Diego CA 92093-0434 United States

ISBN: (纸本)9781424454419

Awareness to a vehicle's surrounding is necessary for safe driving. Current surround technologies focus on the detection of obstacles in hard-to-view places but may neglect temporal information. This paper seeks the causes of dangerous situations by examining surround behavior. A general hierarchical learning framework is introduced to automatically learn surround behaviors. By observing motion trajectories during natural driving, models of rear vehicle behaviors are obtained in an unsupervised fashion. The extracted behaviors are shown to correspond to typical driving scenarios, vehicle overtake and surround overtake, demonstrating the effectiveness of the learning framework. ©2009 IEEE.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

Learning trajectory patterns by clustering: Experimental studies and comparative evaluation

Learning trajectory patterns by clustering: Experimental stu...

引用

Conference on computer vision and Pattern Recognition (CVPR)

作者： Brendan Morris Mohan Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego CA USA

Recently a large amount of research has been devoted to automatic activity analysis. Typically, activities have been defined by their motion characteristics and represented by trajectories. These trajectories are collected and clustered to determine typical behaviors. This paper evaluates different similarity measures and clustering methodologies to catalog their strengths and weaknesses when utilized for the trajectory learning problem. The clustering performance is measured by evaluating the correct clustering rate on different datasets with varying characteristics.

关键词： Principal component analysis Euclidean distance computer vision Prototypes Hidden Markov models Robot vision systems robotics and automation Laboratories Pattern analysis Layout

来源：评论

学校读者我要写书评

暂无评论

Introducing “XMOB”: Extremity Movement Observation Framework for Upper Body Pose Tracking in 3D

Introducing “XMOB”: Extremity Movement Observation Framewo...

引用

IEEE International Symposium on Multimedia

作者： Cuong Tran Mohan M. Trivedi Computer Vision and Robotics Research Laboratory University of California San Diego CA USA

We introduce a vision based, marker less upper body pose tracking approach that first tracks the 3D movements of extremities, including head and hands. Then based on the knowledge of upper body model, these extremity movements are used to predict the whole upper body motion as an inverse kinematics problem. The experimental validation showed the promise of applying this approach in several smart environments and HCI situations, e.g. user activity observation in driving scene, meeting room, teleconference scene.

关键词： Extremities Tracking Head Humans Kinematics Predictive models Layout Laboratories Teleconferencing Motion estimation

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24页 << < 3 4 5 6 7 8 9 10 11 12 > >>

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：