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

569 篇 会议
241 篇 期刊文献
11 册 图书

馆藏范围

821 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

500 篇 工学
- 341 篇 计算机科学与技术...
- 298 篇 软件工程
- 116 篇 信息与通信工程
- 86 篇 生物工程
- 77 篇 光学工程
- 74 篇 机械工程
- 64 篇 控制科学与工程
- 54 篇 生物医学工程（可授...
- 32 篇 化学工程与技术
- 29 篇 仪器科学与技术
- 29 篇 电气工程
- 21 篇 电子科学与技术（可...
- 9 篇 建筑学
- 9 篇 安全科学与工程
- 8 篇 力学（可授工学、理...
- 8 篇 材料科学与工程（可...
- 8 篇 土木工程
298 篇 理学
- 129 篇 数学
- 115 篇 物理学
- 93 篇 生物学
- 39 篇 统计学（可授理学、...
- 33 篇 化学
121 篇 管理学
- 83 篇 图书情报与档案管...
- 45 篇 管理科学与工程(可...
- 13 篇 工商管理
19 篇 医学
- 19 篇 临床医学
- 17 篇 基础医学(可授医学...
- 14 篇 药学(可授医学、理...
17 篇 艺术学
- 17 篇 设计学（可授艺术学...
11 篇 法学
- 11 篇 社会学
4 篇 经济学
2 篇 文学
2 篇 农学
1 篇 教育学

主题

106 篇 pattern recognit...
101 篇 feature extracti...
88 篇 computer vision
81 篇 image segmentati...
67 篇 character recogn...
65 篇 handwriting reco...
62 篇 support vector m...
56 篇 training
46 篇 optical characte...
41 篇 shape
35 篇 accuracy
32 篇 databases
28 篇 histograms
28 篇 testing
27 篇 writing
25 篇 image edge detec...
25 篇 text recognition
25 篇 image recognitio...
21 篇 face recognition
20 篇 hidden markov mo...

机构

206 篇 computer vision ...
43 篇 computer vision ...
42 篇 university of ch...
40 篇 shenzhen key lab...
31 篇 national key lab...
28 篇 faculty of compu...
26 篇 shenzhen key lab...
21 篇 siat branch shen...
19 篇 shanghai ai labo...
18 篇 department of st...
17 篇 computer vision ...
17 篇 computer vision ...
16 篇 sensetime resear...
16 篇 shenzhen key lab...
14 篇 xiamen key labor...
13 篇 school of comput...
12 篇 computer vision ...
12 篇 indian statistic...
11 篇 shanghai artific...
10 篇 department of in...

作者

110 篇 umapada pal
106 篇 pal umapada
59 篇 qiao yu
39 篇 b.b. chaudhuri
32 篇 michael blumenst...
32 篇 palaiahnakote sh...
30 篇 blumenstein mich...
27 篇 yu qiao
27 篇 shivakumara pala...
27 篇 dong chao
26 篇 chaudhuri b.b.
23 篇 u. pal
19 篇 liu xin
18 篇 lu tong
17 篇 wang yali
17 篇 tong lu
16 篇 chanda sukalpa
15 篇 chaudhuri bidyut...
13 篇 fumitaka kimura
13 篇 garain utpal

语言

800 篇 英文
17 篇 其他
4 篇 中文

检索条件"机构=Computer Vision and Pattern Recognition"

共 821 条记录，以下是261-270 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：

Visual Compositional Learning for Human-Object Interaction Detection 16th

Visual Compositional Learning for Human-Object Interaction D...

引用

16th European Conference on computer vision, ECCV 2020

作者： Hou, Zhi Peng, Xiaojiang Qiao, Yu Tao, Dacheng UBTECH Sydney AI Centre School of Computer Science Faculty of Engineering The University of Sydney DarlingtonNSW2008 Australia Shenzhen Key Lab of Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783030585549

Human-Object interaction (HOI) detection aims to localize and infer relationships between human and objects in an image. It is challenging because an enormous number of possible combinations of objects and verbs types forms a long-tail distribution. We devise a deep Visual Compositional Learning (VCL) framework, which is a simple yet efficient framework to effectively address this problem. VCL first decomposes an HOI representation into object and verb specific features, and then composes new interaction samples in the feature space via stitching the decomposed features. The integration of decomposition and composition enables VCL to share object and verb features among different HOI samples and images, and to generate new interaction samples and new types of HOI, and thus largely alleviates the long-tail distribution problem and benefits low-shot or zero-shot HOI detection. Extensive experiments demonstrate that the proposed VCL can effectively improve the generalization of HOI detection on HICO-DET and V-COCO and outperforms the recent state-of-the-art methods on HICO-DET. Code is available at https://***/zhihou7/VCL. © 2020, Springer Nature Switzerland AG.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Proceedings of 2nd International Conference on computer vision & Image Processing 1

引用

丛书名： Advances in Intelligent Systems and Computing

1000年

作者： Bidyut B. Chaudhuri Mohan S. Kankanhalli Balasubramanian Raman

来源：评论

学校读者我要写书评

暂无评论

Head detection and localization from sparse 3D data

Head detection and localization from sparse 3D data

引用

24th German Association for pattern recognition Symposium, DAGM 2002

作者： Clabian, Markus Rötzer, Harald Bischof, Horst Kropatsch, Walter Advanced Computer Vision GmbH Donau City Str.1 ViennaA-1220 Austria Institute for Computer Graphics and Vision Graz University of Technology Inffeldgasse 16 GrazA-8010 Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Computer Science Department Vienna University of Technology Favoritenstr. 9 ViennaA-1040 Austria

ISBN: (纸本)354044209X

Head detection is an important, but difficult task, if no restrictions such as static illumination, frontal face appearance or uniform background can be assumed. We present a system that is able to perform head detection under very general conditions by employing a 3D measurement system namely a structured light distance measurement. An algorithm of head detection from sparse 3D data (19x19 data points) is developed that reconstructs a 3D surface over the image plane and detects head hypotheses of ellipsoidal shape. We demonstrate that detection and rough localization is possible in up to 90% of the images. © Springer-Verlag Berlin Heidelberg 2002.

关键词： computers

来源：评论

学校读者我要写书评

暂无评论

Web Page Classification Algorithm Based on Semi-Supervised Support Vector Machine

Web Page Classification Algorithm Based on Semi-Supervised S...

引用

IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC)

作者： Wenqing Huang Hui You School of Information The Institute of computer vision image processing and pattern recognition acceptable Hangzhou China

ISBN: (数字)9781538618035

ISBN: (纸本)9781538618042

Most web page classification algorithms are learning algorithms under the single-instance single-label framework. Multi-Instance Multi-Label learning is a new machine learning framework. MIMLSVM+ algorithm, using degenerate strategy to transform multiple instances into single instances, and then decomposing multiple labels into a series of two types of classification problems, that is, building an SVM for each label. Because the MIMLSVM+ algorithm degrades the multi-label problem into a series of two types of classification problems, the processing of each label will lose the contact information between the labels independently. Therefore, multi-tasking technology is introduced to make use of the multi-tasking learning framework based on nuclear to validate the MIMLSVM+ expand, get E-MIMLSVM+ algorithm. The paper improves E-MIMLSVM+ algorithm by using the semi-supervised learning method. Experimental results show that the proposed method can achieve higher classification accuracy.

关键词： Support vector machines Classification algorithms Semisupervised learning Web pages Training Supervised learning Machine learning algorithms

来源：评论

学校读者我要写书评

暂无评论

A new wrist vein biometric system

A new wrist vein biometric system

引用

2014 IEEE Symposium Series on Computational Intelligence, IEEE SSCI 2014 - 2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management, CIBIM 2014

作者： Das, Abhijit Pal, Umapada Ballester, Miguel Angel Ferrer Blumenstein, Michael Institute for Integrated and Intelligent Systems Griffith University GriffithQLD Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India IDeTIC University of Las Palmas de Gran Canaria Spain

ISBN: (纸本)9781479945344

In this piece of work a wrist vein pattern recognition and verification system is proposed. Here the wrist vein images from the PUT database were used, which were acquired in visible spectrum. The vein image only highlights the vein pattern area so, segmentation was not required. Since the wrist's veins are not prominent, image enhancement was performed. An Adaptive Histogram Equalization and Discrete Meyer Wavelet were used to enhance the vessel patterns. For feature extraction, the vein pattern is characterized with Dense Local Binary pattern (D-LBP). D-LBP patch descriptors of each training image are used to form a bag of features, which was used to produce the training model. Support Vector Machines (SVMs) were used for classification. An encouraging Equal Error Rate (EER) of 0.79% was achieved in our experiments. © 2014 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

A new efficient and adaptive sclera recognition system

A new efficient and adaptive sclera recognition system

引用

2014 IEEE Symposium Series on Computational Intelligence, IEEE SSCI 2014 - 2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management, CIBIM 2014

ISBN: (纸本)9781479945344

In this paper an efficient and adaptive biometric sclera recognition and verification system is proposed. Sclera segmentation was performed by Fuzzy C-means clustering. Since the sclera vessels are not prominent, in order to make them clearly visible image enhancement was required. Adaptive histogram equalization, followed by a bank of Discrete Meyer Wavelet was used to enhance the sclera vessel patterns. Feature extraction was performed by, Dense Local Directional pattern (D-LDP). D-LDP patch descriptors of each training image are used to form a bag of features;further Spatial Pyramid Matching was used to produce the final training model. Support Vector Machines (SVMs) are used for classification. The UBIRIS version 1 dataset was used here for experimentation of the proposed system. To investigate regarding sclera patterns adaptively with respect to change in environmental condition, population, data accruing technique and time span two different session of the mention dataset are utilized. The images in two sessions are different in acquiring technique, representation, number of individual and they were captured in a gap of two weeks. An encouraging Equal Error Rate (EER) of 3.95% was achieved in the above mention investigation. © 2014 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Fast recovery of piled deformable objects using superquadrics

Fast recovery of piled deformable objects using superquadric...

引用

24th German Association for pattern recognition Symposium, DAGM 2002

作者： Katsoulas, Dimitrios Jaklič, Aleš Institute for Pattern Recognition and Image Processing University of Freiburg Georges-Koehler-Allee 52 FreiburgD-79110 Germany Computer Vision Laboratory University of Ljubljana Tržaška cesta 25 LjubljanaSI-1000 Slovenia

ISBN: (纸本)354044209X

Fast robotic unloading of piled deformable box-like objects (e.g. box-like sacks), is undoubtedly of great importance to the industry. Existing systems although fast, can only deal with layered, neatly placed configurations of such objects. In this paper we discuss an approach which deals with both neatly placed and jumbled configurations of objects. We use a time of flight laser sensor mounted on the hand of a robot for data acquisition. Target objects are modeled with globally deformed superquadrics. Object vertices are detected and superquadric seeds are placed at these vertices. Seed refinement via region growing results in accurate object recovery. Our system exhibits a plethora of advantages the most important of which its speed. Experiments demonstrate that our system can be used for object unloading in real time, when a multi-processor computer is employed. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Data acquisition

来源：评论

学校读者我要写书评

暂无评论

A New Deep Fuzzy Based MSER Model for Multiple Document Images Classification 3rd

A New Deep Fuzzy Based MSER Model for Multiple Document Imag...

引用

3rd International Conference on pattern recognition and Artificial Intelligence, ICPRAI 2022

作者： Biswas, Kunal Shivakumara, Palaiahnakote Sivanthi, Sittravell Pal, Umapada Lu, Yue Liu, Cheng-Lin Ayub, Mohamad Nizam Bin Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai China National Laboratory of Pattern Recognition Institute of Automation of Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy Beijing China

ISBN: (纸本)9783031090363

Understanding document images uploaded on social media is challenging because of multiple types like handwritten, printed and scene text images. This study presents a new model called Deep Fuzzy based MSER for classification of multiple document images (like handwritten, printed and scene text). The proposed model detects candidate components that represent dominant information irrespective of the type of document images by combining fuzzy and MSER in a novel way. For every candidate component, the proposed model extracts distance-based features which result in proximity matrix (feature matrix). Further, the deep learning model is proposed for classification by feeding input images and feature matrix as input. To evaluate the proposed model, we create our own dataset and to show effectiveness, the proposed model is tested on standard datasets. The results show that the proposed approach outperforms the existing methods in terms of average classification rate. © 2022, Springer Nature Switzerland AG.

关键词： Image classification

来源：评论

学校读者我要写书评

暂无评论

PProCRC: Probabilistic Collaboration of Image Patches for Fine-grained Classification

PProCRC: Probabilistic Collaboration of Image Patches for Fi...

引用

International Conference on Image and vision Computing New Zealand, IVCNZ

作者： Tapabrata Chakraborti Brendan McCane Steven Mills Umapada Pal University of Otago tapabrata mccane Computer Vision and Pattern recognition Unit Indian Statistical Institute

ISBN: (数字)9781728185798

ISBN: (纸本)9781728185804

We present a conditional probabilistic framework for collaborative representation of image patches. It incorporates background compensation and outlier patch suppression into the main formulation itself, thus doing away with the need for pre-processing steps to handle the same. A closed form non-iterative solution of the cost function is derived. The proposed method (PProCRC) outperforms earlier CRC formulations: patch based (PCRC, GP-CRC) as well as the state-of-the-art probabilistic (ProCRC and EProCRC) on three fine-grained species recognition datasets (Oxford Flowers, Oxford-IIIT Pets and CUB Birds) using two CNN backbones (Vgg-19 and ResNet-50).

关键词： Visualization Image recognition Collaboration Probabilistic logic Cost function Birds Task analysis

来源：评论

学校读者我要写书评

暂无评论

3-D non-rigid motion estimation from image sequence based on Makov random field [Makov read Markov]

3-D non-rigid motion estimation from image sequence based on...

引用

International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ya-Ming Wang Wen-Qing Huang Kai Zheng Research Center for Computer Vision and Pattern Recognition Zhejiang University of Science and Technology Hangzhou China

ISBN: (纸本)0780384032

We propose an approach to 3-D non-rigid motion estimation from image sequence in this paper. First, with the establishment of feature point correspondence between consecutive image frames, the affine motion model and the central projection model are presented for local non-rigid motion. Then, in order to obtain the global motion parameters and overcome the ill-posed 3-D estimation problem, a framework of Markov random field (MRF) is proposed. By incorporating the motion prior constrains into the MRF, the motion smoothness feature between local regions is reflected. This converts the ill-posed problem into a well-posed one and guarantees a robust solution. Experimental results from a sequence of synthetic image sequence demonstrate the feasibility of the proposed approach.

关键词： Motion estimation Image sequences Shape Deformable models computer vision Parametric statistics Robustness pattern recognition Markov random fields Image converters

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83页 << < 23 24 25 26 27 28 29 30 31 32 > >>

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：