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

6,639 篇 会议
34 篇 期刊文献
5 册 图书

馆藏范围

6,677 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

3,950 篇 工学
- 3,725 篇 计算机科学与技术...
- 1,476 篇 软件工程
- 807 篇 光学工程
- 323 篇 信息与通信工程
- 240 篇 控制科学与工程
- 206 篇 机械工程
- 169 篇 电气工程
- 85 篇 生物医学工程（可授...
- 73 篇 电子科学与技术（可...
- 70 篇 生物工程
- 65 篇 仪器科学与技术
- 38 篇 建筑学
- 36 篇 土木工程
- 34 篇 力学（可授工学、理...
- 32 篇 航空宇航科学与技...
- 29 篇 安全科学与工程
- 23 篇 化学工程与技术
- 21 篇 材料科学与工程（可...
1,498 篇 理学
- 969 篇 物理学
- 929 篇 数学
- 369 篇 统计学（可授理学、...
- 136 篇 生物学
- 40 篇 系统科学
- 26 篇 化学
210 篇 医学
- 210 篇 临床医学
- 23 篇 基础医学(可授医学...
165 篇 管理学
- 123 篇 图书情报与档案管...
- 44 篇 管理科学与工程(可...
- 29 篇 工商管理
21 篇 法学
- 21 篇 社会学
10 篇 农学
9 篇 教育学
6 篇 经济学
2 篇 军事学
1 篇 艺术学

主题

2,364 篇 computer vision
847 篇 pattern recognit...
663 篇 cameras
634 篇 computer science
592 篇 face recognition
555 篇 layout
541 篇 conferences
527 篇 image segmentati...
519 篇 shape
463 篇 object recogniti...
447 篇 robustness
393 篇 humans
340 篇 feature extracti...
320 篇 training
305 篇 object detection
261 篇 image recognitio...
260 篇 application soft...
249 篇 lighting
246 篇 computational mo...
237 篇 image reconstruc...

机构

44 篇 microsoft resear...
27 篇 department of co...
21 篇 swiss fed inst t...
21 篇 school of comput...
21 篇 carnegie mellon ...
20 篇 department of co...
19 篇 swiss fed inst t...
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 center for autom...
14 篇 school of comput...
14 篇 school of comput...
14 篇 computer science...
13 篇 univ maryland co...

作者

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

语言

6,661 篇 英文
9 篇 其他
8 篇 中文

检索条件"任意字段=2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2003"

共 6678 条记录，以下是1261-1270 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：

Semantic Binary Segmentation using Convolutional Networks without Decoders 31

Semantic Binary Segmentation using Convolutional Networks wi...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Aich, Shubhra van der Kamp, William Stavness, Ian Univ Saskatchewan Dept Comp Sci Saskatoon SK Canada

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

In this paper, we propose an efficient architecture for semantic image segmentation using the depth-to-space (D2S) operation. Our D2S model is comprised of a standard CNN encoder followed by a depth-to-space reordering of the final convolutional feature maps. Our approach eliminates the decoder portion of traditional encoder-decoder segmentation models and reduces the amount of computation almost by half. As a participant of the DeepGlobe Road Extraction competition, we evaluate our models on the corresponding road segmentation dataset. Our highly efficient D2S models exhibit comparable performance to standard segmentation models with much lower computational cost.

关键词： Image segmentation Decoding Convolution computer architecture Computational modeling Roads Semantics

来源：评论

学校读者我要写书评

暂无评论

Realtime Quality Assessment of Iris Biometrics under Visible Light 31

Realtime Quality Assessment of Iris Biometrics under Visible...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Jenadeleh, Mohsen Pedersen, Marius Saupe, Dietmar Univ Konstanz Constance Germany Norwegian Univ Sci & Technol Gjovik Norway

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Ensuring sufficient quality of iris images acquired by handheld imaging devices in visible light poses many challenges to iris recognition systems. Many distortions affect the input iris images, and the source and types of these distortions are unknown in uncontrolled environments. We propose a fast no-reference image quality assessment measure for predicting iris image quality to handle severely degraded iris images. The proposed differential signmagnitude statistics index (DSMI) is based on statistical features of the local difference sign-magnitude transform, which are computed by comparing the local mean with the central pixel of the patch and considering the noticeable variations. The experiments, conducted with a reference iris recognition system and three visible light datasets, showed that the quality of iris images strongly affects the recognition performance. Using the proposed method as a quality filtering step improved the performance of the iris recognition system by rejecting poor quality iris samples.

关键词： Iris recognition Image quality Image segmentation Nonlinear distortion Distortion measurement Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Face Verification with Disguise Variations via Deep Disguise Recognizer 31

Face Verification with Disguise Variations via Deep Disguise...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Kohli, Naman Yadav, Daksha Noore, Afzel West Virginia Univ Morgantown WV 26506 USA Texas A&M Univ Kingsville Kingsville TX USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

The performance of current automatic face recognition algorithms is hindered by different covariates such as facial aging, disguises, and pose variations. Specifically, disguises are employed for intentional or unintentional modifications in the facial appearance for hiding one's own identity or impersonating someone else's identity. In this paper, we utilize deep learning based transfer learning approach for face verification with disguise variations. We employ Residual Inception network framework with center loss for learning inherent face representations. The training for the Inception-ResNet model is performed using a large-scale face database which is followed by inductive transfer learning to mitigate the impact of facial disguises. To evaluate the performance of the proposed Deep Disguise Recognizer (DDR) framework, Disguised Faces in the Wild and IIIT-Delhi Disguise Version 1 face databases are used. Experimental evaluation reveals that for the two databases, the proposed DDR framework yields 90.36% and 66.9% face verification accuracy at the false accept rate of 10%.

关键词： Face Databases Face recognition Training Convolution Image recognition

来源：评论

学校读者我要写书评

暂无评论

A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders 31

A Generative Model For Zero Shot Learning Using Conditional ...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Mishra, Ashish Reddy, Shiva Krishna Mittal, Anurag Murthy, Hema A. Indian Inst Technol Madras Chennai Tamil Nadu India

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Zero shot learning in Image Classification refers to the setting where images from some novel classes are absent in the training data but other information such as natural language descriptions or attribute vectors of the classes are available. This setting is important in the real world since one may not be able to obtain images of all the possible classes at training. While previous approaches have tried to model the relationship between the class attribute space and the image space via some kind of a transfer function in order to model the image space correspondingly to an unseen class, we take a different approach and try to generate the samples from the given attributes, using a conditional variational autoencoder, and use the generated samples for classification of the unseen classes. By extensive testing on four benchmark datasets, we show that our model outperforms the state of the art, particularly in the more realistic generalized setting, where the training classes can also appear at the test time along with the novel classes.

关键词： Semantics Training Image generation Decoding Visualization Data models computer vision

来源：评论

学校读者我要写书评

暂无评论

Elastic Handling of Predictor Phase in Functional Regression Models 31

Elastic Handling of Predictor Phase in Functional Regression...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Ahn, Kyungmin Tucker, J. Derek Wu, Wei Srivastava, Anuj Florida State Univ Dept Stat Tallahassee FL 32306 USA Sandia Natl Labs POB 5800 Albuquerque NM 87185 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Functional variables serve important roles as predictors in a variety of pattern recognition and vision applications. Focusing on a specific subproblem, termed scalar-on-function regression, most current approaches adopt the standard L-2 inner product to form a link between functional predictors and scalar responses. These methods may perform poorly when predictor functions contain nuisance phase variability, i.e., predictors are temporally misaligned due to noise. While a simple solution could be to prealign predictors as a pre-processing step, before applying a regression model, this alignment is seldom optimal from the perspective of regression. We propose a new approach, termed elastic functional regression, where alignment is included in the regression model itself, and is performed in conjunction with the estimation of other model parameters. This model is based on a norm-preserving warping of predictors, not the standard time warping of functions, and provides better prediction in situations where the shape or the amplitude of the predictor is more useful than its phase. We demonstrate the effectiveness of this framework using simulated and stock market data.

关键词： Predictive models Measurement Data models Standards Shape Estimation pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Locally-Weighted Elastic Comparison of Planar Shapes 31

Locally-Weighted Elastic Comparison of Planar Shapes

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Strait, Justin Kurtek, Sebastian MacEachern, Steven Ohio State Univ Dept Stat Columbus OH 43210 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Registration of curves is a necessary component of statistical shape analysis. The goal of registration is to align collections of shapes so that common features are appropriately matched for further comparison and subsequent analyses. Traditional methods for registration typically rely on optimizing an energy functional over a set of appropriate shape-preserving transformations (i.e., rotations and re-parameterizations). These functionals typically rely on the standard L-2 metric. In certain applications, it may make sense to use a more flexible metric which can align shapes most preferably with respect to a local shape feature (i.e., a certain curve segment selected from the overall shape). In this work, we define a weighted shape metric which allows for emphasis on local shape features. Registration can be performed with respect to this metric. We demonstrate the registration procedure using simulated curves as well as real data, and show the dependence of the optimal rotation and re-parameterization on the specified weights, as well as the resulting deformation path from one shape to another.

关键词： Shape Measurement Silicon computer vision Standards Strain Beak

来源：评论

学校读者我要写书评

暂无评论

Clothing Change Aware Person Identification 31

Clothing Change Aware Person Identification

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Xue, Jia Meng, Zibo Katipally, Karthik Wang, Haibo van Zon, Kees Rutgers State Univ Dept Elect & Comp Engn New Brunswick NJ 08901 USA Univ South Carolina Dept Comp Sci & Engn Columbia SC USA Philips Res North Amer Cambridge MA USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

We develop a person identification approach - Clothing Change Aware Network (CCAN) for the task of clothing assisted person identification. CCAN concerns approaches that go beyond face recognition and particularly tackles the role of clothing to identification. Person identification is a rather challenging task when clothing appears changed under complex background information. With a pair of two person images as input, CCAN simultaneously performs a verification task to detect change in clothing and an identification task to predict person identity. When clothing from the pair of input images is detected to be different, CCAN automatically understates clothing information while emphasizing face, and vice versa. In practice, CCAN outperforms the way of equally stacking face and full body context features, and shows leading results on the People in Photo Album (PIPA) dataset.

关键词： Clothing Face Task analysis Face recognition Training Cameras

来源：评论

学校读者我要写书评

暂无评论

Finding your Lookalike: Measuring Face Similarity Rather than Face Identity 31

Finding your Lookalike: Measuring Face Similarity Rather tha...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Sadovnik, Amir Gharbi, Wassim Thanh Vu Gallagher, Andrew Lafayette Coll Easton PA 18042 USA Google Res Mountain View CA USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Face images are one of the main areas of focus for computer vision, receiving on a wide variety of tasks. Although face recognition is probably the most widely researched, many other tasks such as kinship detection, facial expression classification and facial aging have been examined. In this work we propose the new, subjective task of quantifying perceived face similarity between a pair of faces. That is, we predict the perceived similarity between facial images, given that they are not of the same person. Although this task is clearly correlated with face recognition, it is different and therefore justifies a separate investigation. Humans often remark that two persons look alike, even in cases where the persons are not actually confused with one another. In addition, because face similarity is different than traditional image similarity, there are challenges in data collection and labeling, and dealing with diverging subjective opinions between human labelers. We present evidence that finding facial look-alikes and recognizing faces are two distinct tasks. We propose a new dataset for facial similarity and introduce the Lookalike network, directed towards similar face classification, which outperforms the ad hoc usage of a face recognition network directed at the same task.

关键词： Face Face recognition Task analysis Training Feature extraction computer vision Neural networks

来源：评论

学校读者我要写书评

暂无评论

Geometry-aware Traffic Flow Analysis by Detection and Tracking 31

Geometry-aware Traffic Flow Analysis by Detection and Tracki...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Shi, Honghui Wang, Zhonghao Zhang, Yang Wang, Xinchao Huang, Thomas UIUC IFP Grp Beckman Inst Champaign IL 61820 USA IBM Res San Jose CA 95120 USA Stevens Inst Technol Hoboken NJ 07030 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

In the second Nvidia AI City Challenge hosted in 2018, the traffic flow analysis challenge proposes an interest task that requires participants to predict the speed of vehicles on road from various traffic camera videos. We propose a simple yet effective method combing both learning based detection and geometric calibration based estimation. We use a learning based method to detect and track vehicles, and use a geometry based camera calibration method to calculate the speed of those vehicles. We achieve a perfect detection rate of target vehicles and a root mean square error (RMSE) of 6.6674 in predicting the vehicle speed, which rank us the third place in the competition.

关键词： Videos Roads Cameras Estimation Tracking computer vision Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

DisguiseNet : A Contrastive Approach for Disguised Face Verification in the Wild 31

DisguiseNet : A Contrastive Approach for Disguised Face Veri...

引用

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Peri, Skand Vishwanath Dhall, Abhinav Indian Inst Technol Ropar Learning Affect & Semant Image Anal LASII Grp Rupnagar Punjab India

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

This paper describes our approach for the Disguised Faces in theWild (DFW) 2018 challenge. The task here is to verify the identity of a person among disguised and impostors images. Given the importance of the task of face verification it is essential to compare methods across a common platform. Our approach is based on VGG-face architecture paired with Contrastive loss based on cosine distance metric. For augmenting the data set, we source more data from the internet. The experiments show the effectiveness of the approach on the DFW data. We show that adding extra data to the DFW dataset with noisy labels also helps in increasing the gen 11 eralization performance of the network. The proposed network achieves 27.13% absolute increase in accuracy over the DFW baseline.

关键词： Face Task analysis Face recognition Feature extraction Visualization Training Noise measurement

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 << < 123 124 125 126 127 128 129 130 131 132 > >>

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：