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

5,349 篇 会议
128 册 图书
29 篇 期刊文献

馆藏范围

5,506 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,747 篇 工学
- 2,253 篇 计算机科学与技术...
- 926 篇 软件工程
- 478 篇 光学工程
- 399 篇 控制科学与工程
- 332 篇 机械工程
- 261 篇 仪器科学与技术
- 250 篇 信息与通信工程
- 128 篇 电气工程
- 122 篇 生物工程
- 90 篇 生物医学工程（可授...
- 70 篇 电子科学与技术（可...
- 39 篇 安全科学与工程
- 33 篇 化学工程与技术
- 31 篇 建筑学
- 27 篇 土木工程
- 25 篇 交通运输工程
- 24 篇 航空宇航科学与技...
858 篇 理学
- 526 篇 物理学
- 439 篇 数学
- 155 篇 统计学（可授理学、...
- 133 篇 生物学
- 28 篇 化学
- 21 篇 系统科学
242 篇 艺术学
- 242 篇 设计学（可授艺术学...
196 篇 管理学
- 101 篇 图书情报与档案管...
- 97 篇 管理科学与工程(可...
- 27 篇 工商管理
96 篇 医学
- 96 篇 临床医学
- 21 篇 基础医学(可授医学...
28 篇 法学
- 26 篇 社会学
8 篇 教育学
6 篇 经济学
5 篇 农学
2 篇 军事学

主题

2,165 篇 computer vision
915 篇 pattern recognit...
890 篇 conferences
640 篇 training
565 篇 cameras
410 篇 feature extracti...
373 篇 computational mo...
364 篇 image segmentati...
350 篇 visualization
338 篇 face recognition
321 篇 computer archite...
309 篇 robustness
290 篇 computer science
287 篇 shape
280 篇 humans
266 篇 object detection
234 篇 layout
196 篇 neural networks
191 篇 application soft...
191 篇 lighting

机构

20 篇 swiss fed inst t...
19 篇 institute for co...
18 篇 university of sc...
18 篇 microsoft resear...
18 篇 swiss fed inst t...
16 篇 carnegie mellon ...
16 篇 chinese acad sci...
14 篇 tsinghua univers...
14 篇 univ sci & techn...
14 篇 carnegie mellon ...
12 篇 harbin inst tech...
12 篇 tsinghua univ pe...
12 篇 department of co...
11 篇 megvii technol p...
11 篇 computer vision ...
11 篇 computer vision ...
10 篇 indian statistic...
10 篇 comp vis ctr bar...
10 篇 school of comput...
10 篇 univ modena & re...

作者

58 篇 timofte radu
17 篇 van gool luc
17 篇 luc van gool
17 篇 horst bischof
16 篇 rita cucchiara
16 篇 radu timofte
14 篇 escalera sergio
14 篇 bischof horst
14 篇 sergio escalera
13 篇 zhigang zhu
13 篇 hugo jair escala...
12 篇 murino vittorio
12 篇 li stan z.
12 篇 chen wei-ting
12 篇 qiang ji
11 篇 cucchiara rita
11 篇 fan haoqiang
11 篇 umapada pal
11 篇 marcos v. conde
11 篇 bowyer kevin w.

语言

5,492 篇 英文
10 篇 中文
5 篇 其他

检索条件"任意字段=2006 Conference on Computer Vision and Pattern Recognition Workshops"

共 5506 条记录，以下是4711-4720 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：

Advanced Concepts for Intelligent vision Systems 2006

引用

丛书名： Lecture Notes in computer Science

2006年

作者： Wilfried Philips Dan Popescu Paul Scheunders

来源：评论

学校读者我要写书评

暂无评论

Shape Topics: A Compact Representation and New Algorithms for 3D Partial Shape Retrieval

Shape Topics: A Compact Representation and New Algorithms fo...

引用

conference on computer vision and pattern recognition (CVPR)

作者： Yi Liu Hongbin Zha Hong Qin National Laboratory on Machine Perception Peking University China Department of Computer Science State University of New York Stony Brook USA

This paper develops an efficient new method for 3D partial shape retrieval. First, a Monte Carlo sampling strategy is employed to extract local shape signatures from each 3D model. After vector quantization, these features are represented by using a bag-of-words model. The main contributions of this paper are threefold as follows: 1) a partial shape dissimilarity measure is proposed to rank shapes according to their distances to the input query, without using any timeconsuming alignment procedure; 2) by applying the probabilistic text analysis technique, a highly compact representation "Shape Topics" and accompanying algorithms are developed for efficient 3D partial shape retrieval, the mapping from "Shape Topics" to "object categories" is established using multi-class SVMs; and 3) a method for evaluating the performance of partial shape retrieval is proposed and tested. To our best knowledge, very few existing methods are able to perform well online partial shape retrieval for large 3D shape repositories. Our experimental results are expected to validate the efficacy and effectiveness of our novel approach.

关键词： Shape measurement Text analysis computer vision Vector quantization Biological system modeling computer aided manufacturing Laboratories computer science Monte Carlo methods Testing

来源：评论

学校读者我要写书评

暂无评论

Monitoring Social Insect Activity with Minimal Human Supervision

Monitoring Social Insect Activity with Minimal Human Supervi...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Tarun Sharma Julian M. Wagner Sara Beery William B. Dickson Michael H. Dickinson Joseph Parker California Institute of Technology USA MIT USA

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Tracking the behavior of animals and their group dynamics in nature offers a crucial look into the delicate ecological networks that compose wildlife diversity. The velvety tree ant (Liometopum occidentale) is an ecologically dominant ant species found in South Western North America; their extensive foraging activity shapes forest communities, and their nests are a biodiversity hot-spot for a multitude of symbiotic invertebrates (myrmecophiles). Despite their vital role in the ecosystem, their activity is largely unstudied. In this work, we develop a multi-sensor camera trap, named ’Ethocam,’ to capture ant behavioral patterns in the field, and combine this technology with a computer vision approach to track colony activity in an undisturbed fashion. We demonstrate an accurate system for counting ants built with minimal human labeling. We show that L. occidentale activity drops rapidly through the morning and study the effect of environmental conditions on ant count. We also report the occurrences of the ants’ interactions with other invertebrates in our camera trap data. Together, these findings demonstrate the potential of our system to capture the behavior of Liometopum occidentale as well as its complex associations with various local species including symbionts, potentially at landscape scale. Our study provides proof of concept for the promise of low-cost remote monitoring of social insect populations.

关键词： Symbiosis computer vision Shape Insects Wildlife Vegetation Cameras

来源：评论

学校读者我要写书评

暂无评论

An Accurate Segmentation-Based Scene Text Detector with Context Attention and Repulsive Text Border

An Accurate Segmentation-Based Scene Text Detector with Cont...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Xi Liu Gaojing Zhou Rui Zhang Xiaolin Wei Meituan-Dianping Group Beijing China

ISBN: (数字)9781728193601

ISBN: (纸本)9781728193618

Scene text detection is one of the most challenging problems in computer vision and has attracted great interest. In general, scene text detection methods are divided into two categories: detection-based and segmentation-based methods. Recently, the segmentation-based methods are more and more popular due to their superior performances and the advantages of detecting arbitrary-shape texts. However, there still exist the following problems: (a) the misclassfication of the unexpected texts, (b) the split of long text lines, (c) the failure of separating very close text instances. In this paper, we propose an accurate segmentation-based detector, which is equipped with context attention and repulsive text border. The context attention incorporates global channel attention, non-local self-attention and spatial attention to better exploit the global and local context, which can greatly increase the discriminative ability for pixels. Due to the enhancement of pixel-level features, false positives and the misdetections of long texts are reduced. Besides, for the purpose of solving very close text instance, a repulsive pixel link, which focuses on the relationships between pixels at the border, is proposed. Experiments on several standard benchmarks, including MSRA-TD500, ICDAR2015, ICDAR2017-MLT and CTW1500, validate the superiority of the proposed method.

关键词： Convolution Decoding Feature extraction Detectors computer vision Benchmark testing Object detection

来源：评论

学校读者我要写书评

暂无评论

A Novel Corner Detector Approach using Sliding Rectangles

A Novel Corner Detector Approach using Sliding Rectangles

引用

ACS/IEEE International conference on computer Systems and Applications

作者： A. Masood M. Sarfraz Computer Science and Engineering Department University of Engineering and Technology Lahore Pakistan Department of Information & Computer Science King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

来源：评论

学校读者我要写书评

暂无评论

Event Detection by Eigenvector Decomposition Using Object and Frame Features

Event Detection by Eigenvector Decomposition Using Object an...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： F. Porikli T. Haga Mitsubishi Electric Research Laboratories Inc. USA

We develop an event detection framework that has two significant advantages over past work. First, we introduce an extended set of time-wise and object-wise statistical features including not only the trajectory coordinates but also the histograms and HMM based representations of object's speed, orientation, location, size, and aspect ratio. These features enable detection of events that cannot be detected with the existing trajectory features reported so far. Second, we introduce a spectral clustering algorithm that can automatically estimate the optimal number of clusters. First, we construct feature-wise affinity matrices from the pair-wise similarity scores of objects using the extended set of features. To determine the usual events, we apply eigen-vector decomposition and obtain object clusters. We show that the number of eigenvectors used in the decomposition is proportional to the optimal number of clusters. Unlike the conventional approaches that try to fit predefined models to events, we analyze the conformity of objects using affinity matrices to find the unusual events. We improve the feature selection process by incorporating feature variances. We prove that the clustering stage is not adversely affected by high dimensionality of data space. Our simulations with synthetic and real data reveal that the proposed detection methods accurately detect usual and unusual events.

关键词： Event detection Hidden Markov models computer vision Matrix decomposition Laboratories Histograms Clustering algorithms Discrete event simulation Supervised learning Legged locomotion

来源：评论

学校读者我要写书评

暂无评论

Expression-Invariant Face recognition with Expression Classification

Expression-Invariant Face Recognition with Expression Classi...

引用

Canadian conference on computer and Robot vision, CRV

作者： Xiaoxing Li G. Mori Hao Zhang School of Computing Science Simon Fraser University Burnaby BC Canada

Face recognition is one of the most intensively studied topics in computer vision and pattern recognition. Facial expression, which changes face geometry, usually has an adverse effect on the performance of a face recognition system. On the other hand, face geometry is a useful cue for recognition. Taking these into account, we utilize the idea of separating geometry and texture information in a face image and model the two types of information by projecting them into separate PCA spaces which are specially designed to capture the distinctive features among different individuals. Subsequently, the texture and geometry attributes are re-combined to form a classifier which is capable of recognizing faces with different expressions. Finally, by studying face geometry, we are able to determine which type of facial expression has been carried out, thus build an expression classifier. Numerical validations of the proposed method are given.

关键词： Face recognition Face detection computer vision Principal component analysis Video sequences Image recognition System testing pattern recognition Information geometry Solid modeling

来源：评论

学校读者我要写书评

暂无评论

Joint Physical-Digital Facial Attack Detection Via Simulating Spoofing Clues

Joint Physical-Digital Facial Attack Detection Via Simulatin...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Xianhua He Dashuang Liang Song Yang Zhanlong Hao Hui Ma Binjie Mao Xi Li Yao Wang Pengfei Yan Ajian Liu Vision AI Department Meituan M.U.S.T MAIS CASIA China

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Face recognition systems are frequently subjected to a variety of physical and digital attacks of different types. Previous methods have achieved satisfactory performance in scenarios that address physical attacks and digital attacks, respectively. However, few methods are considered to integrate a model that simultaneously addresses both physical and digital attacks, implying the necessity to develop and maintain multiple models. To jointly detect physical and digital attacks within a single model, we propose an innovative approach that can adapt to any network architecture. Our approach mainly contains two types of data augmentation, which we call Simulated Physical Spoofing Clues augmentation (SPSC) and Simulated Digital Spoofing Clues augmentation (SDSC). SPSC and SDSC augment live samples into simulated attack samples by simulating spoofing clues of physical and digital attacks, respectively, which significantly improve the capability of the model to detect "unseen" attack types. Extensive experiments show that SPSC and SDSC can achieve state-of-the-art generalization in Protocols 2.1 and 2.2 of the UniAttackData dataset, respectively. Our method won first place in "Unified Physical-Digital Face Attack Detection" of the 5th Face Anti-spoofing Challenge@CVPR2024. Our final submission obtains 3.75% APCER, 0.93% BPCER, and 2.34% ACER, respectively. Our code is available at https://***/Xianhua-He/cvpr2024-face-anti-spoofing-challenge.

关键词： Adaptation models computer vision Protocols Codes Face recognition conferences Computational modeling

来源：评论

学校读者我要写书评

暂无评论

Computational Science and Its Applications - ICCSA 2006 1

引用

丛书名： Lecture Notes in computer Science

1000年

作者： Marina L. Gavrilova Osvaldo Gervasi Vipin Kumar C. J. Kenneth Tan David Taniar Antonio Laganá Youngsong Mun Hyunseung Choo

ISBN: (数字)9783540340744

ISBN: (纸本)9783540340720

This ?ve-volume set was compiled following the 2006 International conference on Computational Science and its Applications, ICCSA 2006, held in Glasgow, UK, during May 8–11, 2006. It represents the outstanding collection of almost 664 refereed papers selected from over 2,450 submissions to ICCSA 2006. Computational science has ?rmly established itself as a vital part of many scienti?c investigations, a?ecting researchers and practitioners in areas ranging from applications such as aerospace and automotive, to emerging technologies such as bioinformatics and nanotechnologies, to core disciplines such as ma- ematics, physics, and chemistry. Due to the shear size of many challenges in computational science, the use of supercomputing, parallel processing, and - phisticated algorithms is inevitable and becomes a part of fundamental theore- cal research as well as endeavors in emerging ?elds. Together, these far-reaching scienti?c areas contributed to shaping this conference in the realms of state-- the-art computational science researchand applications, encompassing the fac- itating theoretical foundations and the innovative applications of such results in other areas.

关键词： Theory of Computation Software Engineering/Programming and Operating Systems Numeric Computing Information Systems and Communication Service Simulation and Modeling computer Imaging, vision, pattern recognition and Graphics

来源：评论

学校读者我要写书评

暂无评论

CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents

CascadeTabNet: An approach for end to end table detection an...

引用

IEEE computer Society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Devashish Prasad Ayan Gadpal Kshitij Kapadni Manish Visave Kavita Sultanpure Pune Institute of Computer Technology India

ISBN: (数字)9781728193601

ISBN: (纸本)9781728193618

An automatic table recognition method for interpretation of tabular data in document images majorly involves solving two problems of table detection and table structure recognition. The prior work involved solving both problems independently using two separate approaches. More recent works signify the use of deep learning-based solutions while also attempting to design an end to end solution. In this paper, we present an improved deep learning-based end to end approach for solving both problems of table detection and structure recognition using a single Convolution Neural Network (CNN) model. We propose CascadeTabNet: a Cascade mask Region-based CNN High-Resolution Network (Cascade mask R-CNN HRNet) based model that detects the regions of tables and recognizes the structural body cells from the detected tables at the same time. We evaluate our results on ICDAR 2013, ICDAR 2019 and Table-Bank public datasets. We achieved 3rd rank in ICDAR 2019 post-competition results for table detection while attaining the best accuracy results for the ICDAR 2013 and Table-Bank dataset. We also attain the highest accuracy results on the ICDAR 2019 table structure recognition dataset. Additionally, we demonstrate effective transfer learning and image augmentation techniques that enable CNNs to achieve very accurate table detection results. Code and dataset has been made available at: https://***/DevashishPrasad/CascadeTabNet.

关键词： Task analysis Image segmentation Semantics Head Predictive models Analytical models 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500页 << < 468 469 470 471 472 473 474 475 476 477 > >>

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：