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

72 篇 会议
1 篇 期刊文献

馆藏范围

73 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

66 篇 工学
- 34 篇 控制科学与工程
- 33 篇 仪器科学与技术
- 27 篇 计算机科学与技术...
- 24 篇 软件工程
- 7 篇 光学工程
- 5 篇 信息与通信工程
- 3 篇 生物工程
- 2 篇 生物医学工程（可授...
- 2 篇 安全科学与工程
- 1 篇 交通运输工程
33 篇 艺术学
- 33 篇 设计学（可授艺术学...
19 篇 理学
- 11 篇 数学
- 7 篇 物理学
- 5 篇 统计学（可授理学、...
- 3 篇 生物学
- 1 篇 地质学
- 1 篇 系统科学
8 篇 管理学
- 8 篇 图书情报与档案管...

主题

21 篇 pattern recognit...
7 篇 image segmentati...
7 篇 feature extracti...
7 篇 training
5 篇 support vector m...
5 篇 decision support...
5 篇 hidden markov mo...
5 篇 local binary pat...
5 篇 optimization
5 篇 semantics
5 篇 face
5 篇 robustness
4 篇 three-dimensiona...
4 篇 videos
4 篇 face recognition
4 篇 benchmark testin...
4 篇 kernel
3 篇 neural networks
3 篇 iterative method...
3 篇 computational mo...

机构

7 篇 cas center for e...
4 篇 center for resea...
4 篇 national laborat...
4 篇 casia center for...
4 篇 computer vision ...
4 篇 casia national l...
3 篇 center for excel...
3 篇 institute of aut...
2 篇 institute of com...
2 篇 toppan printing ...
2 篇 huazhong univers...
2 篇 national laborat...
2 篇 3d impact media ...
2 篇 center for resea...
2 篇 national laborat...
2 篇 department of cs...
2 篇 image and patter...
2 篇 national key lab...
2 篇 dept. of cse iit...
2 篇 department of cs...

作者

5 篇 he ran
4 篇 tan tieniu
4 篇 ran he
3 篇 umapada pal
3 篇 partha pratim ro...
3 篇 tieniu tan
3 篇 huang kaiqi
3 篇 sun zhenan
2 篇 wang liang
2 篇 kaiqi huang
2 篇 zhenan sun
2 篇 deng weihong
2 篇 cheng-lin liu
2 篇 zhang man
2 篇 takafumi aoki
2 篇 liang wang
2 篇 li qi
2 篇 cao dong
2 篇 man zhang
2 篇 ayan das

语言

72 篇 英文
1 篇 中文

检索条件"任意字段=3rd IAPR Asian Conference on Pattern Recognition, ACPR 2015"

共 73 条记录，以下是51-60 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：

Global and local consistent multi-view subspace clustering

Global and local consistent multi-view subspace clustering

引用

asian conference on pattern recognition (acpr)

作者： Yanbo Fan Ran He Bao-Gang Hu CASIA National Laboratory of Pattern Recognition CASIA Center for Research on Intelligent Perception and Computing CAS Center for Excellence in Brain Science and Intelligence Technology

ISBN: (纸本)9781479961016

Multi-view clustering aims to cluster data with multiple sources of information. Comparing with single view clustering, it is challenging to make use of the extra information embedded in multiple views. This paper presents a multi-view subspace clustering method (MSC-GL) by simultaneously combining both the global low-rank constraint and local cross topology preserving constraints. The global constraint maximizes the correlation between representational matrices while encouraging each of them to be low rank. The local constraints enable representational matrices under different views to share local structure information. An efficiently iterative algorithm is developed to minimize the proposed joint learning problem, and extensive experiments on five multi-view benchmarks demonstrate that the proposed model outperforms the state-of-the-art multiview clustering methods.

关键词： Topology Clustering methods Clustering algorithms Databases Correlation Iterative methods Benchmark testing

来源：评论

学校读者我要写书评

暂无评论

Uniform low-rank representation for unsupervised visual domain adaptation

Uniform low-rank representation for unsupervised visual doma...

引用

asian conference on pattern recognition (acpr)

作者： Pengcheng Liu Peipei Yang Kaiqi Huang Tieniu Tan Center for Research on Intelligent Perception and Computing Chinese Academy of Sciences

ISBN: (纸本)9781479961016

Visual domain adaptation aims to adapt a model learned in source domain to target domain, which has received much attention in recent years. In this paper, we propose a uniform low-rank representation based unsupervised domain adaptation method which captures the intrinsic relationship among the source and target samples and meanwhile eliminates the disturbance from the noises and outliers. In particular, we first align the source and target samples into a common subspace using a subspace alignment technique. Then we learn a domain-invariant dictionary with respect to the transformed source and target samples. Finally, all the transformed samples are low-rank represented based on the learned dictionary. Extensive experimental results show that our method is beneficial to reducing the domain difference, and we achieve the state-of-the-art performance on the widely used visual domain adaptation benchmark.

关键词： Dictionaries Visualization Object recognition Adaptation models Benchmark testing pattern recognition Computational modeling

来源：评论

学校读者我要写书评

暂无评论

Supervised topology preserving hashing

Supervised topology preserving hashing

引用

asian conference on pattern recognition (acpr)

作者： Shu Zhang Man Zhang Qi Li Tieniu Tan Ran He CASIA National Laboratory of Pattern Recognition CASIA Center for Research on Intelligent Perception and Computing CAS Center for Excellence in Brain Science and Intelligence Technology

ISBN: (纸本)9781479961016

Learning based hashing is gaining traction in large-scale retrieval systems. It aims to learn compact binary codes that can preserve semantic similarity in the hamming space. This paper presents a supervised topology hashing (SPTH) algorithm to learn compact binary codes that can exploit both the supervisory information as well as the local topology structure of datasets. To build a connection between the original space and the resultant hamming space, we minimize the quantization errors together with a classification error term and a topology preserving term. A nonlinear kernel feature space is further used to improve the generalization power. An alternating iterative algorithm is developed to minimize the complex objective function that contains both continuous and discrete variables. Experimental results on three benchmark datasets demonstrate the effectiveness of the proposed method on image retrieval tasks.

关键词： Topology Binary codes Optimization Kernel Semantics Quantization (signal) Linear programming

来源：评论

学校读者我要写书评

暂无评论

Joint space learning for video-based face recognition

Joint space learning for video-based face recognition

引用

asian conference on pattern recognition (acpr)

作者： Dong Cao Ran He Zhenan Sun Tieniu Tan CASIA National Laboratory of Pattern Recognition CASIA Center for Research on Intelligent Perception and Computing CAS Center for Excellence in Brain Science and Intelligence Technology

ISBN: (纸本)9781479961016

Popularity of surveillance and mobile cameras provides great opportunities to video-based face recognition (VFR) in less-controlled conditions. This paper proposes a joint space learning method to simultaneously identify the most representative samples and discriminative features from facial videos for reliable face recognition. Specifically, we use a mixture modal by learning multiple feature spaces to capture the data variations where the representative samples in each subspace are learned. Actually, this procedure is a chick to egg problem and an alternate algorithm is developed to monotonically optimize the joint task. In addition, randomized techniques are applied to kernel approximations for capturing the nonlinear structure in data, so that both accuracy and efficiency of our method can be improved. The proposed method performs better than the state-of-the-art video based face recognition methods on Honda, Mobo and YouTube Celebrities databases.

关键词： Videos Face Face recognition Kernel Training Learning systems YouTube

来源：评论

学校读者我要写书评

暂无评论

On coupled regularization for non-convex variational image enhancement

On coupled regularization for non-convex variational image e...

引用

asian conference on pattern recognition (acpr)

作者： Freddie Åström Christoph Schnorr Heidelberg Collaboratory for Image Processing Heidelberg University Germany Image and Pattern Analysis Group Heidelberg University Germany

A natural continuation from conventional convex methods for image enhancement is the transition to non-convex formulations. However, strictly non-convex models do not admit traditional tools from convex optimization to be used. To resolve this drawback, non-convex problems are often cast into convex formulations by relaxing stringent assumptions on model properties. In this work we present an alternative approach. We study when an energy functional is convex given a non-convex penalty term. Key to our formulation is the introduction of a novel coupling between the discretization scheme and a non-local weight function in the data term. We interpret the non-local weights for the finite difference operators. In a denoising application we study a class of non-convex ℓ p -norms. The resulting energies are globally minimized using the popular ADMM.

关键词： Couplings Minimization Uncertainty Robustness Image enhancement Convex functions Noise reduction

来源：评论

学校读者我要写书评

暂无评论

Structure-driven facade parsing with irregular patterns

Structure-driven facade parsing with irregular patterns

引用

asian conference on pattern recognition (acpr)

作者： Jinglu Wang Chun Liu Tianwei Shen Long Quan The Hong Kong University of Science and Technology NavInfo Co. Ltd

ISBN: (纸本)9781479961016

We propose a novel method for recognizing irregular patterns in facades. An irregular pattern is an incomplete 2D grid, representing the placements of repetitive structural architectural objects (e.g., windows), which is capable of being generalized to a variety of facade structures. To effectively recognize such a pattern, we jointly model objects and object structures in a unified Marked Point Process framework, where the architectural objects are abstracted as sparsely populated geometric entities and the pairwise spatially interactions are modeled as elliptical repulsion fields. To optimize the proposed model, we introduce a structure-driven Monte Carlo Markov Chain (MCMC) sampler, by which the irregular pattern hypotheses are iteratively constructed in a bottom-up manner and verified in a top-down manner. The solution space is explored more efficiently for fast convergence. Extensive experiments have shown the efficiency and accuracy of our method of parsing a large category of facades.

关键词： Three-dimensional displays Grammar Layout Optimization pattern recognition Lattices Mathematical model

来源：评论

学校读者我要写书评

暂无评论

Handwritten word spotting in Indic scripts using foreground and background information

Handwritten word spotting in Indic scripts using foreground ...

引用

asian conference on pattern recognition (acpr)

作者： Ayan Das Ayan Kumar Bhunia Partha Pratim Roy Umapada Pal Dept. of ECE IEM Kolkata India Dept. of CSE IIT Roorkee India CVPR Unit ISI Kolkata India

ISBN: (纸本)9781479961016

In this paper we present a line based word spotting system based on Hidden Markov Model for offline Indic scripts such as Bangla (Bengali) and Devanagari. We propose a novel approach of combining foreground and background information of text line images for keyword-spotting by character filler models. The candidate keywords are searched from a line without segmenting character or words. A significant improvement in performance is noted by using both foreground and background information than anyone alone. Pyramid Histogram of Oriented Gradient (PHOG) feature has been used in our word spotting framework and it outperforms other existing features of word spotting. The framework of combining foreground and background information has been evaluated in IAM dataset (English script) to show the robustness of the proposed approach.

关键词： Decision support systems Hidden Markov models pattern recognition Image segmentation Histograms Robustness Training

来源：评论

学校读者我要写书评

暂无评论

High order graphlets for pattern classification

High order graphlets for pattern classification

引用

asian conference on pattern recognition (acpr)

作者： Anjan Dutta Hichem Sahbi LTCI Université Paris-Sacley Paris France

ISBN: (纸本)9781479961016

Graph-based methods are known to be successful for pattern description and comparison. Their general principle consists in using graphs to model local features as well as their structural relationships and achieving pattern comparison with graph matching. Among these methods, subgraph isomorphism is particularly effective but intractable for general and unconstrained graph structures. In this paper, we introduce an efficient and effective method for graph-based pattern comparison. The main contribution includes a new stochastic search procedure that allows us to efficiently extract, hash and measure the distribution of increasing order subgraphs (a.k.a graphlets) in large graph collections. We consider both low and high order graphlets in order to model local features as well as their complex interactions. These graphlets are partitioned into sets of isomorphic and non-isomorphic subgraphs using well designed hash functions with a low probability of collision; resulting into accurate graph descriptions. When combined with support vector machines, these high order graphlet-based descriptions have positive impact on the performance of pattern comparison and classification as corroborated through experiments on different standard databases.

关键词： Dictionaries Kernel Complexity theory Feature extraction Stochastic processes Support vector machines Search problems

来源：评论

学校读者我要写书评

暂无评论

Mirrored non-maximum suppression for accurate object part localization

Mirrored non-maximum suppression for accurate object part lo...

引用

asian conference on pattern recognition (acpr)

作者： Lianrui Fu Junge Zhang Kaiqi Huang National Laboratory of Pattern Recognition Center for Research on Intelligent Perception and Computing Institute of Automation Chinese Academy of Sciences CAS Center for Excellence in Brain Science and Intelligence Technology

ISBN: (纸本)9781479961016

There has been significant progress in object part localization such as human pose estimation and facial landmark detection. In most of the previous methods, two phenomena are ignored. Firstly, they usually output a set of candidate pose hypotheses but the hypothesis with the highest score obtained by Non-Maximum Suppression (NMS) is not always the optimal result. Secondly, they can not get exactly bilaterally symmetric keypoints on the mirrored images even though the training data is always augmented with mirrored images. In fact, the intrinsic relationship between the original image and the mirrored one is helpful for object part localization. In this paper, we propose Mirrored Non-Maximum Suppression (Mirrored NMS) which can utilize mirrored detections to improve the accuracy of object part localization. Experimental results show that our method can improve the state-of-the-art accuracy by 1.3~3.0% in PCP for human pose estimation and can produce more accurate results than averaging multiple hypotheses for facial landmark detection.

关键词： Mirrors Face Robustness pattern recognition Training data

来源：评论

学校读者我要写书评

暂无评论

Mid-level parts mined by feature selection for action recognition

Mid-level parts mined by feature selection for action recogn...

引用

asian conference on pattern recognition (acpr)

作者： ShiWei Zhang Nong Sang ChangXin Gao FeiFei Chen Jing Hu Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology China

ISBN: (纸本)9781479961016

This paper develops a method to learn very few discriminative part detectors from training videos directly, for action recognition. We hold the opinion that being discriminative to action classification is of primary importance in selecting part detectors, not just intuitive. For this purpose, part selection based on feature selection is proposed, employing SVM method. Firstly, large number of candidate detectors are trained using k-means and Exemplar-LDA techniques in whitened feature space. Secondly, each candidate part detector is regarded as a visual feature, so that detector selection can be achieved by feature selection. Detectors with larger weight, indicating more discriminative, will be selected. Meanwhile, to keep space-volume structure information, we use the novel method saliency-driven pooling to form feature primitives which are concatenated into mid-level feature vector. Finally, we conduct experiments on three challenging action datasets (KTH, Olympic Sports, HMDB51) and the results outperform the state-of-the-art.

关键词： Detectors Feature extraction Videos Support vector machines Semantics pattern recognition Image 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8页 << < 1 2 3 4 5 6 7 8 > >>

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：