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

676 篇 会议
144 篇 期刊文献
130 册 图书
8 篇 学位论文

馆藏范围

958 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

634 篇 工学
- 464 篇 计算机科学与技术...
- 210 篇 软件工程
- 141 篇 电气工程
- 126 篇 机械工程
- 114 篇 光学工程
- 71 篇 控制科学与工程
- 48 篇 仪器科学与技术
- 40 篇 信息与通信工程
- 20 篇 电子科学与技术（可...
- 15 篇 生物医学工程（可授...
- 14 篇 生物工程
- 12 篇 材料科学与工程（可...
- 10 篇 测绘科学与技术
- 8 篇 化学工程与技术
- 8 篇 航空宇航科学与技...
- 7 篇 土木工程
- 7 篇 安全科学与工程
- 6 篇 建筑学
- 6 篇 交通运输工程
272 篇 理学
- 205 篇 物理学
- 89 篇 数学
- 27 篇 统计学（可授理学、...
- 15 篇 生物学
- 10 篇 系统科学
62 篇 医学
- 60 篇 临床医学
42 篇 管理学
- 24 篇 图书情报与档案管...
- 19 篇 管理科学与工程(可...
37 篇 艺术学
- 37 篇 设计学（可授艺术学...
9 篇 法学
- 9 篇 社会学
7 篇 农学
- 7 篇 作物学
2 篇 教育学

主题

261 篇 computer vision
233 篇 pattern recognit...
79 篇 artificial intel...
74 篇 image processing...
62 篇 feature extracti...
49 篇 computer imaging...
44 篇 image segmentati...
43 篇 face recognition
43 篇 images
41 篇 information syst...
39 篇 visualization
35 篇 computer graphic...
35 篇 algorithm analys...
33 篇 cameras
31 篇 training
28 篇 conferences
28 篇 image color anal...
28 篇 user interfaces ...
26 篇 histograms
24 篇 databases

机构

20 篇 national laborat...
14 篇 computer vision ...
9 篇 huazhong univ sc...
9 篇 institute for pa...
8 篇 computer vision ...
6 篇 chinese acad sci...
6 篇 department of st...
4 篇 shenzhen key lab...
4 篇 department of in...
4 篇 huazhong univ sc...
4 篇 microsoft resear...
4 篇 huazhong univ sc...
4 篇 national laborat...
4 篇 chinese acad sci...
4 篇 college of compu...
4 篇 computer and vis...
3 篇 the ohio state u...
3 篇 queen’s universi...
3 篇 multimedia engin...
3 篇 institute of pat...

作者

11 篇 sang nong
10 篇 umapada pal
10 篇 tian jinwen
8 篇 cao zhiguo
7 篇 bischof horst
7 篇 huang kaiqi
6 篇 li dehua
6 篇 tieniu tan
6 篇 tan tieniu
5 篇 j. k. aggarwal
5 篇 kaiqi huang
5 篇 zhang tianxu
5 篇 horst bischof
5 篇 alireza alaei
5 篇 aggarwal j.k.
4 篇 gabor fichtinger
4 篇 gian luca forest...
4 篇 cai chao
4 篇 sebastian bauer
4 篇 huang yongzhen

语言

910 篇 英文
34 篇 中文
13 篇 其他
1 篇 法文

检索条件"任意字段=MIPPR 2011: Pattern Recognition and Computer Vision"

共 958 条记录，以下是521-530 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：

A Study of Nesterov's Scheme for Lagrangian Decomposition and MAP Labeling

A Study of Nesterov's Scheme for Lagrangian Decomposition an...

引用

IEEE Conference on computer vision and pattern recognition

作者： Bogdan Savchynskyy Jorg Kappes Stefan Schmidt Christoph Schnorr HCI Heidelberg University IPA Heidelberg University

ISBN: (纸本)9781457703942

We study the MAP-labeling problem for graphical models by optimizing a dual problem obtained by Lagrangian decomposition. In this paper, we focus specifically on Nesterov's optimal first-order optimization scheme for non-smooth convex programs, that has been studied for a range of other problems in computer vision and machine learning in recent years. We show that in order to obtain an efficiently convergent iteration, this approach should be augmented with a dynamic estimation of a corresponding Lipschitz constant, leading to a runtime complexity of O(1/∈) in terms of the desired precision ∈. Additionally, we devise a stopping criterion based on a duality gap as a sound basis for competitive comparison and show how to compute it efficiently. We evaluate our results using the publicly available Middlebury database and a set of computer generated graphical models that highlight specific aspects, along with other state-of-the-art methods for MAP-inference.

关键词： images computer vision Lagrangian Graphical models decomposition manufacturing automation protocol MITIGATION ACTION PLANS computers

来源：评论

学校读者我要写书评

暂无评论

Intelligent recognition of Texture and Material Properties of Fabrics

Intelligent Recognition of Texture and Material Properties o...

引用

作者： Wang, Xin University of Ottawa

学位级别：master

Fabrics are unique materials which consist of various properties affecting their performance and end-uses. A computerized fabric property evaluation and analysis method plays a crucial role not only in textile industry but also in scientific research. An accurate analysis and measurement of fabric property provides a powerful tool for gauging product quality, assuring regulatory compliance and assessing the performance of textile *** thesis investigated the solutions for applying computerized methods to evaluate and intelligently interpret the texture and material properties of fabric in an inexpensive and efficient way. Firstly, a method which allows automatic recognition of basic weave pattern and precisely measuring the yarn count is proposed. The yarn crossed-areas are segmented by a spatial domain integral projection approach. Combining fuzzy c-means (FCM) and principal component analysis (PCA) on grey level co-occurrence matrix (GLCM) feature vectors extracted from the segments enables to classify detected segments into two clusters. Based on the analysis on texture orientation features, the yarn crossed-area states are automatically determined. An autocorrelation method is used to find weave repeats and correct detection errors. The method was validated by using computer simulated woven samples and real woven fabric images. The test samples have various yarn counts, appearance, and weave types. All weave patterns of tested fabric samples are successfully recognized and computed yarn counts are consistent to the manual ***, we present a methodology for using the high resolution 3D surface data of fabric samples to measure surface roughness in a nondestructive and accurate way. A parameter FDFFT, which is the fractal dimension estimation from 2DFFT of 3D surface scan, is proposed as the indicator of surface roughness. The robustness of FDFFT, which consists of the rotation-invariance and scale-invariance, is validated on a number of comp

关键词： Texture Fabric SVM computer vision Neural network Fractal dimension pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Generalized Gaussian Process Models

Generalized Gaussian Process Models

引用

IEEE Conference on computer vision and pattern recognition

作者： Antoni B. Chan Daxiang Dong Department of Computer Science City University of Hong Kong

ISBN: (纸本)9781457703942

We propose a generalized Gaussian process model (GGPM), which is a unifying framework that encompasses many existing Gaussian process (GP) models, such as GP regression, classification, and counting. In the GGPM framework, the observation likelihood of the GP model is itself parameterized using the exponential family distribution. By deriving approximate inference algorithms for the generalized GP model, we are able to easily apply the same algorithm to all other GP models. Novel GP models are created by changing the parameterization of the likelihood function, which greatly simplifies their creation for task-specific output domains. We also derive a closed-form efficient Taylor approximation for inference on the model, and draw interesting connections with other model-specific closed-form approximations. Finally, using the GGPM, we create several new GP models and show their efficacy in building task-specific GP models for computer vision.

关键词： GRAPHIC PANEL Geometric progression Likelihood Functions Gaussian processes Inference algorithms Gauss images computer vision

来源：评论

学校读者我要写书评

暂无评论

Non-Rigid Structure from Motion with Complementary Rank-3 Spaces

Non-Rigid Structure from Motion with Complementary Rank-3 Sp...

引用

IEEE Conference on computer vision and pattern recognition

作者： Paulo F. U. Gotardo Aleix M. Martinez Department of Electrical and Computer Engineering The Ohio State University

ISBN: (纸本)9781457703942

Non-rigid structure from motion (NR-SFM) is a difficult, underconstrained problem in computer vision. This paper proposes a new algorithm that revises the standard matrix factorization approach in NR-SFM. We consider two alternative representations for the linear space spanned by a small number K of 3D basis shapes. As compared to the standard approach using general rank-3K matrix factors, we show that improved results are obtained by explicitly modeling K complementary spaces of rank-3. Our new method is positively compared to the state-of-the-art in NRSFM, providing improved results on high-frequency deformations of both articulated and simpler deformable shapes. We also present an approach for NR-SFM with occlusion.

关键词： images computer vision matrix decomposition Complementary Occlusion ARTICULATED Potassium

来源：评论

学校读者我要写书评

暂无评论

3D object retrieval with semantic attributes 11

3D object retrieval with semantic attributes

引用

19th ACM International Conference on Multimedia ACM Multimedia 2011, MM'11

作者： Gong, Boqing Liu, Jianzhuang Wang, Xiaogang Tang, Xiaoou Department of Information Engineering Chinese University of Hong Kong Hong Kong Department of Electronic Engineering Chinese University of Hong Kong Hong Kong Shenzhen Key Laboratory for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

ISBN: (纸本)9781450306164

Humans are capable of describing objects using attributes, such as "the object looks circular and is man-made". Motivated by these high-level descriptions, we build a user-friendly 3D object retrieval system, where the user can browse the database and search for targeted objects using semantic attributes. The main advantage of our system is that it does not require the user to find or sketch a 3D object as the query for 3D object retrieval. Besides, to the best of our knowledge, our system has obtained the best retrieval performance on three popular benchmarks. Copyright 2011 ACM.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Modeling Human Activities as Speech

Modeling Human Activities as Speech

引用

IEEE Conference on computer vision and pattern recognition

作者： Chia-Chih Chen J. K. Aggarwal Computer & Vision Research Center/Department of ECE The University of Texas at Austin

ISBN: (纸本)9781457703942

Human activity recognition and speech recognition appear to be two loosely related research areas. However, on a careful thought, there are several analogies between activity and speech signals with regard to the way they are generated, propagated, and perceived. In this paper, we propose a novel action representation, the action spectrogram, which is inspired by a common spectrographic representation of speech. Different from sound spectrogram, an action spectrogram is a space-time-frequency representation which characterizes the short-time spectral properties of body parts' movements. While the essence of the speech signal is the variation of air pressure in time, our method models activities as the likelihood time series of action associated local interest patterns. This low-level process is realized by learning boosted window classifiers from spatially quantized spatio-temporal interest features. We have tested our algorithm on a variety of human activity datasets and achieved superior results.

关键词： Human Activities Speech Voice Signal Spectrogram Interest groups Air Pressure Essences Speech recognition SOUND Vibration Hearing

来源：评论

学校读者我要写书评

暂无评论

Human Action recognition Using DFT

Human Action Recognition Using DFT

引用

National Conference on computer vision, pattern recognition, Image Processing and Graphics (NCVPRIPG)

作者： Sonal Kumari Suman K. Mitra Birla Institute of Technology and Science Pilani Rajasthan India Dhirubhai Ambani Institute of Information and Communication Technology Gandhinagar Gujarat India

Action is any meaningful movement of the human and it is used to convey information or to interact naturally without any mechanical devices. Human action recognition is motivated by some of the applications such as video retrieval, Human robot interaction, to interact with deaf and dumb people etc. In any Action recognition System, some pre-processing steps are done for removing the noise caused because of illumination effects, blurring, false contour etc. Background subtraction is done to remove the static or slowly varying background. In this paper, multiple background subtraction algorithms are tested and then one of them is selected for the further process of action recognition. Background subtraction is also known as foreground/background segmentation or foreground extraction. The next step is the feature extraction which deals with the extraction of the important feature (like corner points, optical flow, shape, motion vectors etc.) from the image frame. The proposed novel action recognition algorithm uses discrete Fourier transform (DFT) of the small image block.

关键词： Discrete Fourier transforms Feature extraction Humans computer vision Classification algorithms Databases Adaptation models

来源：评论

学校读者我要写书评

暂无评论

computer vision/computer Graphics Collaboration Techniques 1

引用

丛书名： Lecture Notes in computer Science 6930

2011年

作者： André Gagalowicz,Wilfried Philips

ISBN: (数字)9783642241369

ISBN: (纸本)9783642241352

This book constitutes the refereed proceedings of the 5th International Conference on computer vision/computer Graphics Collaboration Techniques, MIRAGE 2011, held in Rocquencourt, France, in October 2011. The 23 full papers presented were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics with focus on computer vision/computer Graphics Collaboration Techniques involving image analysis/synthesis approaches especially concerning theoretical, computational, experimental or industrial aspects of model-based image analysis and image-based model synthesis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Variable Grouping for Energy Minimization

Variable Grouping for Energy Minimization

引用

IEEE Conference on computer vision and pattern recognition

作者： Taesup Kim Sebastian Nowozin Pushmeet Kohli Chang D. Yoo Dept. of Electrical Engineering KAIST Microsoft Research Cambridge

ISBN: (纸本)9781457703942

This paper addresses the problem of efficiently solving large-scale energy minimization problems encountered in computer vision. We propose an energy-aware method for merging random variables to reduce the size of the energy to be minimized. The method examines the energy function to find groups of variables which are likely to take the same label in the minimum energy state and thus can be represented by a single random variable. We propose and evaluate a number of extremely efficient variable grouping strategies. Experimental results show that our methods result in a dramatic reduction in the computational cost and memory requirements (in some cases by a factor of one hundred) with almost no drop in the accuracy of the final result. Comparative evaluation with efficient super-pixel generation methods, which are commonly used in variable grouping, reveals that our methods are far superior both in terms of accuracy and running time.

关键词： Energy sources Random variable ENERGY MINIMISATION memory requirements Energy level Runtime images computer vision

来源：评论

学校读者我要写书评

暂无评论

Finding the Weakest Link in Person Detectors

Finding the Weakest Link in Person Detectors

引用

IEEE Conference on computer vision and pattern recognition

作者： Devi Parikh C. Lawrence Zitnick Toyota Technological Institute Chicago (TTIC) Microsoft Research

ISBN: (纸本)9781457703942

Detecting people remains a popular and challenging problem in computer vision. In this paper, we analyze parts-based models for person detection to determine which components of their pipeline could benefit the most if improved. We accomplish this task by studying numerous detectors formed from combinations of components performed by human subjects and machines. The parts-based model we study can be roughly broken into four components: feature detection, part detection, spatial part scoring and contextual reasoning including non-maximal suppression. Our experiments conclude that part detection is the weakest link for challenging person detection datasets. Non-maximal suppression and context can also significantly boost performance. However, the use of human or machine spatial models does not significantly or consistently affect detection accuracy.

关键词： WEAK LINK Persons images computer vision detector human subject pipeline machine

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96页 << < 49 50 51 52 53 54 55 56 57 58 > >>

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：