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

6,421 篇 会议
25 篇 期刊文献
3 册 图书

馆藏范围

6,448 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

3,849 篇 工学
- 3,647 篇 计算机科学与技术...
- 1,431 篇 软件工程
- 790 篇 光学工程
- 302 篇 信息与通信工程
- 242 篇 控制科学与工程
- 219 篇 电气工程
- 201 篇 机械工程
- 80 篇 生物医学工程（可授...
- 68 篇 生物工程
- 67 篇 电子科学与技术（可...
- 64 篇 仪器科学与技术
- 36 篇 建筑学
- 33 篇 力学（可授工学、理...
- 33 篇 土木工程
- 33 篇 航空宇航科学与技...
- 26 篇 安全科学与工程
- 22 篇 交通运输工程
- 20 篇 材料科学与工程（可...
- 18 篇 化学工程与技术
1,453 篇 理学
- 945 篇 物理学
- 890 篇 数学
- 352 篇 统计学（可授理学、...
- 134 篇 生物学
- 38 篇 系统科学
- 23 篇 化学
160 篇 管理学
- 110 篇 图书情报与档案管...
- 52 篇 管理科学与工程(可...
- 25 篇 工商管理
112 篇 医学
- 112 篇 临床医学
17 篇 法学
- 17 篇 社会学
12 篇 农学
8 篇 教育学
7 篇 艺术学
6 篇 经济学
2 篇 军事学

主题

2,288 篇 computer vision
789 篇 pattern recognit...
637 篇 cameras
629 篇 computer science
568 篇 face recognition
555 篇 layout
510 篇 image segmentati...
509 篇 conferences
498 篇 shape
445 篇 robustness
439 篇 object recogniti...
388 篇 humans
332 篇 feature extracti...
321 篇 training
303 篇 object detection
262 篇 image recognitio...
257 篇 application soft...
246 篇 lighting
238 篇 image reconstruc...
237 篇 computational mo...

机构

41 篇 microsoft resear...
26 篇 department of co...
21 篇 swiss fed inst t...
21 篇 school of comput...
20 篇 department of co...
19 篇 swiss fed inst t...
19 篇 carnegie mellon ...
18 篇 department of co...
17 篇 department of in...
17 篇 the robotics ins...
17 篇 institute of com...
16 篇 univ sci & techn...
16 篇 robotics institu...
15 篇 tsinghua univ pe...
14 篇 department of el...
14 篇 school of comput...
14 篇 school of comput...
13 篇 univ maryland co...
13 篇 microsoft resear...
13 篇 microsoft resear...

作者

39 篇 timofte radu
28 篇 s.k. nayar
24 篇 huang thomas s.
23 篇 xiaoou tang
22 篇 t. kanade
20 篇 t.s. huang
19 篇 van gool luc
19 篇 t. darrell
19 篇 chellappa rama
18 篇 nayar shree k.
17 篇 a.k. jain
17 篇 a. zisserman
17 篇 jain anil k.
16 篇 g. healey
16 篇 torralba antonio
16 篇 heung-yeung shum
16 篇 zisserman andrew
16 篇 l. van gool
15 篇 m. shah
15 篇 ji qiang

语言

6,445 篇 英文
4 篇 其他

检索条件"任意字段=1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 1992"

共 6449 条记录，以下是1591-1600 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：

EmotioNet: An accurate, real-time algorithm for the automatic annotation of a million facial expressions in the wild

EmotioNet: An accurate, real-time algorithm for the automati...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Benitez-Quiroz, C. Fabian Srinivasan, Ramprakash Martinez, Aleix M. Dept. Electrical and Computer Engineering Ohio State University United States

ISBN: (纸本)9781467388511

Research in face perception and emotion theory requires very large annotated databases of images of facial expressions of emotion. Annotations should include Action Units (AUs) and their intensities as well as emotion category. This goal cannot be readily achieved manually. Herein, we present a novel computer vision algorithm to annotate a large database of one million images of facial expressions of emotion in the wild (i.e., face images downloaded from the Internet). First, we show that this newly proposed algorithm can recognize AUs and their intensities reliably across databases. To our knowledge, this is the first published algorithm to achieve highly-accurate results in the recognition of AUs and their intensities across multiple databases. Our algorithm also runs in real-time (>30 images/second), allowing it to work with large numbers of images and video sequences. Second, we use WordNet to download 1,000,000 images of facial expressions with associated emotion keywords from the Internet. These images are then automatically annotated with AUs, AU intensities and emotion categories by our algorithm. The result is a highly useful database that can be readily queried using semantic descriptions for applications in computer vision, affective computing, social and cognitive psychology and neuroscience; e.g., "show me all the images with happy faces" or "all images with AU 1 at intensity c".

关键词： Behavioral research

来源：评论

学校读者我要写书评

暂无评论

Constrained joint cascade regression framework for simultaneous facial action unit recognition and facial landmark detection

Constrained joint cascade regression framework for simultane...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Wu, Yue Ji, Qiang ECSE Department Rensselaer Polytechnic Institute 110 8th street TroyNY United States

ISBN: (纸本)9781467388511

Cascade regression framework has been shown to be effective for facial landmark detection. It starts from an initial face shape and gradually predicts the face shape update from the local appearance features to generate the facial landmark locations in the next iteration until convergence. In this paper, we improve upon the cascade regression framework and propose the Constrained Joint Cascade Regression Framework (CJCRF) for simultaneous facial action unit recognition and facial landmark detection, which are two related face analysis tasks, but are seldomly exploited together. In particular, we first learn the relationships among facial action units and face shapes as a constraint. Then, in the proposed constrained joint cascade regression framework, with the help from the constraint, we iteratively update the facial landmark locations and the action unit activation probabilities until convergence. Experimental results demonstrate that the intertwined relationships of facial action units and face shapes boost the performances of both facial action unit recognition and facial landmark detection. The experimental results also demonstrate the effectiveness of the proposed method comparing to the state-of-the-art works.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Discriminatively embedded K-means for multi-view clustering

Discriminatively embedded K-means for multi-view clustering

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Xu, Jinglin Han, Junwei Nie, Feiping School of Automation Center for OPTIMAL Northwestern Polytechnical University Xi'an710072 China School of Computer Science Center for OPTIMAL Northwestern Polytechnical University Xi'an710072 China

ISBN: (纸本)9781467388511

In real world applications, more and more data, for example, image/video data, are high dimensional and represented by multiple views which describe different perspectives of the data. Efficiently clustering such data is a challenge. To address this problem, this paper proposes a novel multi-view clustering method called Discriminatively Embedded K-Means (DEKM), which embeds the synchronous learning of multiple discriminative subspaces into multiview K-Means clustering to construct a unified framework, and adaptively control the intercoordinations between these subspaces simultaneously. In this framework, we firstly design a weighted multi-view Linear Discriminant Analysis (LDA), and then develop an unsupervised optimization scheme to alternatively learn the common clustering indicator, multiple discriminative subspaces and weights for heterogeneous features with convergence. Comprehensive evaluations on three benchmark datasets and comparisons with several state-of-the-art multi-view clustering algorithms demonstrate the superiority of the proposed work.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Facial expression intensity estimation using ordinal information

Facial expression intensity estimation using ordinal informa...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Zhao, Rui Gan, Quan Wang, Shangfei Ji, Qiang Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute United States School of Computer Science and Technology University of Science and Technology of China China

ISBN: (纸本)9781467388511

Previous studies on facial expression analysis have been focused on recognizing basic expression categories. There is limited amount of work on the continuous expression intensity estimation, which is important for detecting and tracking emotion change. Part of the reason is the lack of labeled data with annotated expression intensity since expression intensity annotation requires expertise and is time consuming. In this work, we treat the expression intensity estimation as a regression problem. By taking advantage of the natural onset-apex-offset evolution pattern of facial expression, the proposed method can handle different amounts of annotations to perform frame-level expression intensity estimation. In fully supervised case, all the frames are provided with intensity annotations. In weakly supervised case, only the annotations of selected key frames are used. While in unsupervised case, expression intensity can be estimated without any annotations. An efficient optimization algorithm based on Alternating Direction Method of Multipliers (ADMM) is developed for solving the optimization problem associated with parameter learning. We demonstrate the effectiveness of proposed method by comparing it against both fully supervised and unsupervised approaches on benchmark facial expression datasets.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Aggregating image and text quantized correlated components

Aggregating image and text quantized correlated components

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Tran, Thi Quynh Nhi Le Borgne, Herve Crucianu, Michel CEA LIST CEDRIC-CNAM France CEA LIST Gif-sur-Yvette France CEDRIC-CNAM Paris France

ISBN: (纸本)9781467388511

Cross-modal tasks occur naturally for multimedia content that can be described along two or more modalities like visual content and text. Such tasks require to "translate" information from one modality to another. Methods like kernelized canonical correlation analysis (KCCA) attempt to solve such tasks by finding aligned subspaces in the description spaces of different modalities. Since they favor correlations against modality-specific information, these methods have shown some success in both cross-modal and bi-modal tasks. However, we show that a direct use of the subspace alignment obtained by KCCA only leads to coarse translation abilities. To address this problem, we first put forward a new representation method that aggregates information provided by the projections of both modalities on their aligned subspaces. We further suggest a method relying on neighborhoods in these subspaces to complete uni-modal information. Our proposal exhibits state-of-the-art results for bi-modal classification on Pascal VOC07 and improves it by over 60% for cross-modal retrieval on FlickR 8K/30K.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

On benefits of selection diversity via bilevel exclusive sparsity

On benefits of selection diversity via bilevel exclusive spa...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Yang, Haichuan Huang, Yijun Tran, Lam Liu, Ji Huang, Shuai Department of Computer Science University of Rochester United States Goergen Institute for Data Science University of Rochester United States Department of Industrial and Systems Engineering University of Washington United States

ISBN: (纸本)9781467388511

Sparse feature (dictionary) selection is critical for various tasks in computer vision, machine learning, and pattern recognition to avoid overfitting. While extensive research efforts have been conducted on feature selection using sparsity and group sparsity, we note that there has been a lack of development on applications where there is a particular preference on diversity. That is, the selected features are expected to come from different groups or categories. This diversity preference is motivated from many real-world applications such as advertisement recommendation, privacy image classification, and design of survey. In this paper, we proposed a general bilevel exclusive sparsity formulation to pursue the diversity by restricting the overall sparsity and the sparsity in each group. To solve the proposed formulation that is NP hard in general, a heuristic procedure is proposed. The main contributions in this paper include: 1) A linear convergence rate is established for the proposed algorithm; 2) The provided theoretical error bound improves the approaches such as L1norm and L0types methods which only use the overall sparsity and the quantitative benefits of using the diversity sparsity is provided. To the best of our knowledge, this is the first work to show the theoretical benefits of using the diversity sparsity; 3) Extensive empirical studies are provided to validate the proposed formulation, algorithm, and theory.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Recovering the missing link: Predicting class-attribute associations for unsupervised zero-shot learning

Recovering the missing link: Predicting class-attribute asso...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Al-Halah, Ziad Tapaswi, Makarand Stiefelhagen, Rainer Karlsruhe Institute of Technology Karlsruhe76131 Germany

ISBN: (纸本)9781467388511

Collecting training images for all visual categories is not only expensive but also impractical. Zero-shot learning (ZSL), especially using attributes, offers a pragmatic solution to this problem. However, at test time most attributebased methods require a full description of attribute associations for each unseen class. Providing these associations is time consuming and often requires domain specific knowledge. In this work, we aim to carry out attributebased zero-shot classification in an unsupervised manner. We propose an approach to learn relations that couples class embeddings with their corresponding attributes. Given only the name of an unseen class, the learned relationship model is used to automatically predict the classattribute associations. Furthermore, our model facilitates transferring attributes across data sets without additional effort. Integrating knowledge from multiple sources results in a significant additional improvement in performance. We evaluate on two public data sets: Animals with Attributes and aPascal/aYahoo. Our approach outperforms state-ofthe-art methods in both predicting class-attribute associations and unsupervised ZSL by a large margin.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Video2GIF: Automatic generation of animated GIFs from video

Video2GIF: Automatic generation of animated GIFs from video

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Gygli, Michael Song, Yale Cao, Liangliang CVL ETH Zurich Zurich Switzerland Yahoo Research New York United States

ISBN: (纸本)9781467388511

We introduce the novel problem of automatically generating animated GIFs from video. GIFs are short looping video with no sound, and a perfect combination between image and video that really capture our attention. GIFs tell a story, express emotion, turn events into humorous moments, and are the new wave of photojournalism. We pose the question: Can we automate the entirely manual and elaborate process of GIF creation by leveraging the plethora of user generated GIF content?We propose a Robust Deep RankNet that, given a video, generates a ranked list of its segments according to their suitability as GIF. We train our model to learn what visual content is often selected for GIFs by using over 100K user generated GIFs and their corresponding video sources. We effectively deal with the noisy web data by proposing a novel adaptive Huber loss in the ranking formulation. We show that our approach is robust to outliers and picks up several patterns that are frequently present in popular animated GIFs. On our new large-scale benchmark dataset, we show the advantage of our approach over several state-of-the-art methods.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Summary transfer: Exemplar-based subset selection for video summarization

Summary transfer: Exemplar-based subset selection for video ...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Zhang, Ke Chao, Wei-Lun Sha, Fei Grauman, Kristen University of Southern California Los AngelesCA90089 United States University of California Los AngelesCA90095 United States University of Texas at Austin AustinTX78701 United States

ISBN: (纸本)9781467388511

Video summarization has unprecedented importance to help us digest, browse, and search today's ever-growing video collections. We propose a novel subset selection technique that leverages supervision in the form of humancreated summaries to perform automatic keyframe-based video summarization. The main idea is to nonparametrically transfer summary structures from annotated videos to unseen test videos. We show how to extend our method to exploit semantic side information about the video's category/genre to guide the transfer process by those training videos semantically consistent with the test input. We also show how to generalize our method to subshot-based summarization, which not only reduces computational costs but also provides more flexible ways of defining visual similarity across subshots spanning several frames. We conduct extensive evaluation on several benchmarks and demonstrate promising results, outperforming existing methods in several settings.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

Weakly supervised object localization with progressive domain adaptation

Weakly supervised object localization with progressive domai...

引用

2016 ieee conference on computer vision and pattern recognition, cvpr 2016

作者： Li, Dong Huang, Jia-Bin Li, Yali Wang, Shengjin Yang, Ming-Hsuan Tsinghua University China University of Illinois Urbana-Champaign United States University of California Merced United States

ISBN: (纸本)9781467388511

We address the problem of weakly supervised object localization where only image-level annotations are available for training. Many existing approaches tackle this problem through object proposal mining. However, a substantial amount of noise in object proposals causes ambiguities for learning discriminative object models. Such approaches are sensitive to model initialization and often converge to an undesirable local minimum. In this paper, we address this problem by progressive domain adaptation with two main steps: classification adaptation and detection adaptation. In classification adaptation, we transfer a pre-trained network to our multi-label classification task for recognizing the presence of a certain object in an image. In detection adaptation, we first use a mask-out strategy to collect class-specific object proposals and apply multiple instance learning to mine confident candidates. We then use these selected object proposals to fine-tune all the layers, resulting in a fully adapted detection network. We extensively evaluate the localization performance on the PASCAL VOC and ILSVRC datasets and demonstrate significant performance improvement over the state-of-the-art methods.

关键词： pattern recognition

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500页 << < 156 157 158 159 160 161 162 163 164 165 > >>

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：