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

1,535 篇 会议
21 册 图书
13 篇 期刊文献

馆藏范围

1,569 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,449 篇 工学
- 1,046 篇 计算机科学与技术...
- 655 篇 机械工程
- 358 篇 电气工程
- 111 篇 软件工程
- 55 篇 控制科学与工程
- 49 篇 信息与通信工程
- 35 篇 光学工程
- 28 篇 仪器科学与技术
- 17 篇 网络空间安全
- 15 篇 生物工程
- 9 篇 生物医学工程（可授...
- 8 篇 电子科学与技术（可...
- 8 篇 安全科学与工程
- 7 篇 测绘科学与技术
- 4 篇 化学工程与技术
- 3 篇 建筑学
112 篇 医学
- 108 篇 临床医学
- 6 篇 基础医学(可授医学...
- 4 篇 特种医学
87 篇 理学
- 38 篇 物理学
- 34 篇 数学
- 24 篇 生物学
- 12 篇 统计学（可授理学、...
- 9 篇 系统科学
- 5 篇 化学
42 篇 管理学
- 32 篇 图书情报与档案管...
- 10 篇 管理科学与工程(可...
24 篇 艺术学
- 24 篇 设计学（可授艺术学...
19 篇 法学
- 19 篇 社会学
15 篇 文学
- 15 篇 新闻传播学
2 篇 教育学
2 篇 农学
1 篇 经济学

主题

528 篇 computer vision
139 篇 face recognition
135 篇 pattern recognit...
135 篇 feature extracti...
130 篇 cameras
129 篇 image segmentati...
128 篇 object recogniti...
115 篇 object detection
103 篇 training
98 篇 robustness
94 篇 images
92 篇 image recognitio...
90 篇 shape
90 篇 layout
84 篇 visualization
77 篇 image reconstruc...
76 篇 humans
70 篇 computer science
66 篇 computational mo...
66 篇 image classifica...

机构

23 篇 rhein westfal th...
18 篇 carnegie mellon ...
16 篇 chinese acad sci...
15 篇 stanford univ st...
14 篇 univ chinese aca...
11 篇 australian natl ...
11 篇 univ calif berke...
10 篇 univ sci & techn...
10 篇 mit cambridge ma...
10 篇 univ maryland co...
9 篇 microsoft res as...
9 篇 univ washington ...
8 篇 microsoft resear...
8 篇 microsoft res re...
8 篇 natl univ singap...
7 篇 chinese univ hon...
7 篇 tech univ munich...
6 篇 mpi intelligent ...
6 篇 kaust thuwal
6 篇 imperial coll lo...

作者

20 篇 leibe bastian
12 篇 ji qiang
10 篇 li stan z.
9 篇 pal umapada
8 篇 zhang lei
8 篇 chellappa rama
8 篇 lei zhen
8 篇 zafeiriou stefan...
8 篇 hu weiming
8 篇 hua gang
7 篇 ramanan deva
7 篇 wang xiaogang
7 篇 yan shuicheng
7 篇 mubarak shah
6 篇 van gool luc
6 篇 darrell trevor
6 篇 luiten jonathon
6 篇 pollefeys marc
6 篇 bischof horst
6 篇 ghanem bernard

语言

1,554 篇 英文
9 篇 土耳其文
2 篇 日文
2 篇 其他
1 篇 西班牙文
1 篇 中文

检索条件"任意字段=26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR"

共 1569 条记录，以下是131-140 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：

Harry Potter's Marauder's Map: Localizing and Tracking Multiple Persons-of-Interest by Nonnegative Discretization

Harry Potter's Marauder's Map: Localizing and Tracking Multi...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Yu, Shoou-, I Yang, Yi Hauptmann, Alexander Carnegie Mellon Univ 5000 Forbes Ave Pittsburgh PA 15213 USA

ISBN: (纸本)9780769549897

A device just like Harry Potter's Marauder's Map, which pinpoints the location of each person-of-interest at all times, provides invaluable information for analysis of surveillance videos. To make this device real, a system would be required to perform robust person localization and tracking in real world surveillance scenarios, especially for complex indoor environments with many walls causing occlusion and long corridors with sparse surveillance camera coverage. We propose a tracking-by-detection approach with nonnegative discretization to tackle this problem. Given a set of person detection outputs, our framework takes advantage of all important cues such as color, person detection, face recognition and non-background information to perform tracking. Local learning approaches are used to uncover the manifold structure in the appearance space with spatio-temporal constraints. Nonnegative discretization is used to enforce the mutual exclusion constraint, which guarantees a person detection output to only belong to exactly one individual. Experiments show that our algorithm performs robust localization and tracking of persons-of-interest not only in outdoor scenes, but also in a complex indoor real-world nursing home environment.

关键词： computer graphics face recognition image colour analysis image sensors object detection object tracking video surveillance

来源：评论

学校读者我要写书评

暂无评论

A Fast Approximate AIB Algorithm for Distributional Word Clustering

A Fast Approximate AIB Algorithm for Distributional Word Clu...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Wang, Lei Zhang, Jianjia Zhou, Luping Li, Wanqing Univ Wollongong Sch Comp Sci & Software Engn Wollongong NSW 2522 Australia

ISBN: (纸本)9780769549897

Distributional word clustering merges the words having similar probability distributions to attain reliable parameter estimation, compact classification models and even better classification performance. Agglomerative Information Bottleneck (AIB) is one of the typical word clustering algorithms and has been applied to both traditional text classification and recent image recognition. Although enjoying theoretical elegance, AIB has one main issue on its computational efficiency, especially when clustering a large number of words. Different from existing solutions to this issue, we analyze the characteristics of its objective function - the loss of mutual information, and show that by merely using the ratio of word-class joint probabilities of each word, good candidate word pairs for merging can be easily identified. Based on this finding, we propose a fast approximate AIB algorithm and show that it can significantly improve the computational efficiency of AIB while well maintaining or even slightly increasing its classification performance. Experimental study on both text and image classification benchmark data sets shows that our algorithm can achieve more than 100 times speedup on large real data sets over the state-of-the-art method.

关键词： approximation theory image classification pattern clustering probability text analysis

来源：评论

学校读者我要写书评

暂无评论

MKPLS: Manifold Kernel Partial Least Squares for Lipreading and Speaker Identification

MKPLS: Manifold Kernel Partial Least Squares for Lipreading ...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Bakry, Amr Elgammal, Ahmed Rutgers State Univ Dept Comp Sci Piscataway NJ 08854 USA

ISBN: (纸本)9780769549897

Visual speech recognition is a challenging problem, due to confusion between visual speech features. the speaker identification problem is usually coupled with speech recognition. Moreover, speaker identification is important to several applications, such as automatic access control, biometrics, authentication, and personal privacy issues. In this paper, we propose a novel approach for lipreading and speaker identification. We propose a new approach for manifold parameterization in a low-dimensional latent space, where each manifold is represented as a point in that space. We initially parameterize each instance manifold using a nonlinear mapping from a unified manifold representation. We then factorize the parameter space using Kernel Partial Least Squares (KPLS) to achieve a low-dimension manifold latent space. We use two-way projections to achieve two manifold latent spaces, one for the speech content and one for the speaker. We apply our approach on two public databases: AVLetters and OuluVS. We show the results for three different settings of lipreading: speaker independent, speaker dependent, and speaker semi-dependent. Our approach outperforms for the speaker semi-dependent setting by at least 15% of the baseline, and competes in the other two settings.

关键词： audio-visual systems feature extraction least squares approximations speaker recognition

来源：评论

学校读者我要写书评

暂无评论

Designing Category-Level Attributes for Discriminative Visual recognition

Designing Category-Level Attributes for Discriminative Visua...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Yu, Felix X. Cao, Liangliang Feris, Rogerio S. Smith, John R. Chang, Shih-Fu Columbia Univ New York NY 10027 USA IBM Corp Thomas J Watson Res Ctr Yorktown Hts NY 10598 USA

ISBN: (纸本)9780769549897

Attribute-based representation has shown great promises for visual recognition due to its intuitive interpretation and cross-category generalization property. However, human efforts are usually involved in the attribute designing process, making the representation costly to obtain. In this paper, we propose a novel formulation to automatically design discriminative "category-level attributes", which can be efficiently encoded by a compact category-attribute matrix. the formulation allows us to achieve intuitive and critical design criteria (category-separability, learnability) in a principled way. the designed attributes can be used for tasks of cross-category knowledge transfer, achieving superior performance over well-known attribute dataset Animals with Attributes (AwA) and a large-scale ILSVRC2010 dataset (1.2M images). this approach also leads to state-of-the-art performance on the zero-shot learning task on AwA.

关键词： data visualisation learning (artificial intelligence) matrix algebra object recognition

来源：评论

学校读者我要写书评

暂无评论

Saliency Aggregation: A Data-driven Approach

Saliency Aggregation: A Data-driven Approach

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Mai, Long Niu, Yuzhen Liu, Feng Portland State Univ Dept Comp Sci Portland OR 97207 USA

ISBN: (纸本)9780769549897

A variety of methods have been developed for visual saliency analysis. these methods often complement each other. this paper addresses the problem of aggregating various saliency analysis methods such that the aggregation result outperforms each individual one. We have two major observations. First, different methods perform differently in saliency analysis. Second, the performance of a saliency analysis method varies with individual images. Our idea is to use data-driven approaches to saliency aggregation that appropriately consider the performance gaps among individual methods and the performance dependence of each method on individual images. this paper discusses various data-driven approaches and finds that the image-dependent aggregation method works best. Specifically, our method uses a Conditional Random Field (CRF) framework for saliency aggregation that not only models the contribution from individual saliency map but also the interaction between neighboring pixels. To account for the dependence of aggregation on an individual image, our approach selects a subset of images similar to the input image from a training data set and trains the CRF aggregation model only using this subset instead of the whole training set. Our experiments on public saliency benchmarks show that our aggregation method outperforms each individual saliency method and is robust with the selection of aggregated methods.

关键词： computer vision learning (artificial intelligence)

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Joint Object Discovery and Segmentation in Internet Images

Unsupervised Joint Object Discovery and Segmentation in Inte...

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Rubinstein, Michael Joulin, Armand Kopf, Johannes Liu, Ce MIT CSAIL Cambridge MA 02139 USA INRIA Paris France Microsoft Res Beijing Peoples R China

ISBN: (纸本)9780769549897

We present a new unsupervised algorithm to discover and segment out common objects from large and diverse image collections. In contrast to previous co-segmentation methods, our algorithm performs well even in the presence of significant amounts of noise images (images not containing a common object), as typical for datasets collected from Internet search. the key insight to our algorithm is that common object patterns should be salient within each image, while being sparse with respect to smooth transformations across images. We propose to use dense correspondences between images to capture the sparsity and visual variability of the common object over the entire database, which enables us to ignore noise objects that may be salient within their own images but do not commonly occur in others. We performed extensive numerical evaluation on established co-segmentation datasets, as well as several new datasets generated using Internet search. Our approach is able to effectively segment out the common object for diverse object categories, while naturally identifying images where the common object is not present.

关键词： Internet image recognition image retrieval image segmentation object recognition

来源：评论

学校读者我要写书评

暂无评论

Fast Trust Region for Segmentation

Fast Trust Region for Segmentation

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Gorelick, Lena Schmidt, Frank R. Boykov, Yuri Univ Western Ontario Comp Vis Grp London ON N6A 3K7 Canada Univ Freiburg BIOSS Ctr Biol Signalling Studies Freiburg Germany

ISBN: (纸本)9780769549897

Trust region is a well-known general iterative approach to optimization which offers many advantages over standard gradient descent techniques. In particular, it allows more accurate nonlinear approximation models. In each iteration this approach computes a global optimum of a suitable approximation model within a fixed radius around the current solution, a.k.a. trust region. In general, this approach can be used only when some efficient constrained optimization algorithm is available for the selected nonlinear (more accurate) approximation model. In this paper we propose a Fast Trust Region (FTR) approach for optimization of segmentation energies with nonlinear regional terms, which are known to be challenging for existing algorithms. these energies include, but are not limited to, KL divergence and Bhattacharyya distance between the observed and the target appearance distributions, volume constraint on segment size, and shape prior constraint in a form of.. 2 distance from target shape moments. Our method is 1-2 orders of magnitude faster than the existing state-of-the-art methods while converging to comparable or better solutions.

关键词： computer vision convergence image segmentation iterative methods optimisation

来源：评论

学校读者我要写书评

暂无评论

From N to N+1: Multiclass Transfer Incremental Learning

From N to N+1: Multiclass Transfer Incremental Learning

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Kuzborskij, Ilja Orabona, Francesco Caputo, Barbara Idiap Res Inst Martigny Switzerland Ecole Polytech Fed Lausanne Lausanne Switzerland Toyota Technol Inst Chicago IL USA

ISBN: (纸本)9780769549897

Since the seminal work of thrun [17], the learning to learn paradigm has been defined as the ability of an agent to improve its performance at each task with experience, with the number of tasks. Within the object categorization domain, the visual learning community has actively declined this paradigm in the transfer learning setting. Almost all proposed methods focus on category detection problems, addressing how to learn a new target class from few samples by leveraging over the known source. But if one thinks of learning over multiple tasks, there is a need for multiclass transfer learning algorithms able to exploit previous source knowledge when learning a new class, while at the same time optimizing their overall performance. this is an open challenge for existing transfer learning algorithms. the contribution of this paper is a discriminative method that addresses this issue, based on a Least-Squares Support Vector Machine formulation. Our approach is designed to balance between transferring to the new class and preserving what has already been learned on the source models. Extensive experiments on subsets of publicly available datasets prove the effectiveness of our approach.

关键词： computer vision data handling learning (artificial intelligence) least squares approximations support vector machines

来源：评论

学校读者我要写书评

暂无评论

Histogram of Weighted Local Directions for Gait recognition

Histogram of Weighted Local Directions for Gait Recognition

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Sivapalan, Sabesan Chen, Daniel Denman, Simon Sridharan, Sridha Fookes, Clinton Queensland Univ Technol Image & Video Res Lab Brisbane Qld 4001 Australia

ISBN: (纸本)9780769549903

In this paper, we explore the effectiveness of patch-based gradient feature extraction methods when applied to appearance-based gait recognition. Extending existing popular feature extraction methods such as HOG and LDP, we propose a novel technique which we term the Histogram of Weighted Local Directions (HWLD). these 3 methods are applied to gait recognition using the GEI feature, with classification performed using SRC. Evaluations on the CASIA and OULP datasets show significant improvements using these patch-based methods over existing implementations, with the proposed method achieving the highest recognition rate for the respective datasets. In addition, the HWLD can easily be extended to 3D, which we demonstrate using the GEV feature on the DGD dataset, observing improvements in performance.

关键词： feature extraction gait analysis image recognition

来源：评论

学校读者我要写书评

暂无评论

Scalable Sparse Subspace Clustering

Scalable Sparse Subspace Clustering

引用

26th ieee conference on computer vision and pattern recognition (cvpr)

作者： Peng, Xi Zhang, Lei Yi, Zhang Sichuan Univ Coll Comp Sci Machine Intelligence Lab Chengdu 610065 Peoples R China

ISBN: (纸本)9780769549897

In this paper, we address two problems in Sparse Sub-space Clustering algorithm (SSC), i.e., scalability issue and out-of-sample problem. SSC constructs a sparse similarity graph for spectral clustering by using l(1)-minimization based coefficients, has achieved state-of-the-art results for image clustering and motion segmentation. However, the time complexity of SSC is proportion to the cubic of problem size such that it is inefficient to apply SSC into large scale setting. Moreover, SSC does not handle with out-of-sample data that are not used to construct the similarity graph. For each new datum, SSC needs recalculating the cluster membership of the whole data set, which makes SSC is not competitive in fast online clustering. To address the problems, this paper proposes out-of-sample extension of SSC, named as Scalable Sparse Subspace Clustering (SSSC), which makes SSC feasible to cluster large scale data sets. the solution of SSSC adopts a "sampling, clustering, coding, and classifying" strategy. Extensive experimental results on several popular data sets demonstrate the effectiveness and efficiency of our method comparing with the state-of-the-art algorithms.

关键词： computational complexity graph theory image classification image coding image motion analysis image sampling image segmentation pattern clustering

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157页 << < 10 11 12 13 14 15 16 17 18 19 > >>

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：