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

22,998 篇 会议
107 册 图书
93 篇 期刊文献

馆藏范围

23,197 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

13,621 篇 工学
- 11,107 篇 计算机科学与技术...
- 3,478 篇 软件工程
- 2,445 篇 机械工程
- 1,715 篇 光学工程
- 1,076 篇 电气工程
- 1,013 篇 控制科学与工程
- 784 篇 信息与通信工程
- 411 篇 仪器科学与技术
- 352 篇 生物工程
- 251 篇 生物医学工程（可授...
- 196 篇 电子科学与技术（可...
- 114 篇 化学工程与技术
- 107 篇 安全科学与工程
- 100 篇 测绘科学与技术
- 88 篇 建筑学
- 85 篇 交通运输工程
- 84 篇 土木工程
3,494 篇 医学
- 3,481 篇 临床医学
- 81 篇 基础医学(可授医学...
3,240 篇 理学
- 1,939 篇 物理学
- 1,639 篇 数学
- 563 篇 统计学（可授理学、...
- 500 篇 生物学
- 249 篇 系统科学
- 106 篇 化学
521 篇 管理学
- 311 篇 图书情报与档案管...
- 223 篇 管理科学与工程(可...
- 76 篇 工商管理
276 篇 艺术学
- 276 篇 设计学（可授艺术学...
66 篇 法学
- 63 篇 社会学
38 篇 农学
28 篇 教育学
22 篇 经济学
10 篇 军事学
3 篇 文学

主题

10,186 篇 computer vision
3,967 篇 pattern recognit...
3,005 篇 training
2,007 篇 computational mo...
1,817 篇 visualization
1,815 篇 cameras
1,515 篇 feature extracti...
1,481 篇 shape
1,455 篇 three-dimensiona...
1,438 篇 image segmentati...
1,287 篇 robustness
1,205 篇 computer archite...
1,155 篇 semantics
1,147 篇 conferences
1,107 篇 layout
1,093 篇 computer science
1,088 篇 object detection
1,025 篇 benchmark testin...
970 篇 codes
922 篇 face recognition

机构

136 篇 univ sci & techn...
121 篇 univ chinese aca...
118 篇 chinese univ hon...
107 篇 carnegie mellon ...
101 篇 tsinghua univers...
101 篇 microsoft resear...
95 篇 swiss fed inst t...
93 篇 zhejiang univ pe...
82 篇 university of sc...
81 篇 zhejiang univers...
80 篇 university of ch...
77 篇 shanghai ai lab ...
72 篇 shanghai jiao to...
69 篇 national laborat...
67 篇 microsoft res as...
67 篇 alibaba grp peop...
64 篇 adobe research
62 篇 tsinghua univ pe...
60 篇 peking univ peop...
59 篇 univ oxford oxfo...

作者

81 篇 van gool luc
72 篇 timofte radu
64 篇 zhang lei
47 篇 luc van gool
40 篇 yang yi
40 篇 li stan z.
37 篇 loy chen change
34 篇 chen chen
33 篇 xiaoou tang
32 篇 liu yang
32 篇 qi tian
31 篇 tian qi
31 篇 sun jian
30 篇 murino vittorio
30 篇 pascal fua
29 篇 darrell trevor
29 篇 li fei-fei
28 篇 li xin
28 篇 ying shan
27 篇 vasconcelos nuno

语言

23,131 篇 英文
38 篇 其他
22 篇 中文
5 篇 土耳其文
2 篇 日文

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

共 23198 条记录，以下是321-330 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：

Towards efficient feature sharing in MIMO architectures

Towards efficient feature sharing in MIMO architectures

引用

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

作者： Sun, Remy Rame, Alexandre Masson, Clement Thome, Nicolas Cord, Matthieu Sorbonne Univ MLIA ISIR Paris France Conservatoire Natl Arts & Metiers CEDRIC Vertigo Paris France Thales Land & Air Syst Elancourt France Valeo Ai Paris France

ISBN: (纸本)9781665487399

Multi-input multi-output architectures propose to train multiple subnetworks within one base network and then average the subnetwork predictions to benefit from ensembling for free. Despite some relative success, these architectures are wasteful in their use of parameters. Indeed, we highlight in this paper that the learned subnetwork fail to share even generic features which limits their applicability on smaller mobile and AR/VR devices. We posit this behavior stems from an ill-posed part of the multi-input multi-output framework. To solve this issue, we propose a novel unmixing step in MIMO architectures that allows subnetworks to properly share features. Preliminary experiments on CIFAR 100 show our adjustments allow feature sharing and improve model performance for small architectures.

关键词： Performance evaluation computer vision Impedance matching conferences Neural networks computer architecture pattern recognition

来源：评论

学校读者我要写书评

暂无评论

SAM: Pushing the Limits of Saliency Prediction Models 31

SAM: Pushing the Limits of Saliency Prediction Models

引用

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

作者： Cornia, Marcella Baraldi, Lorenzo Serra, Giuseppe Cmcidara, Rita Univ Modena & Reggio Emilia Modena Italy Univ Udine Udine Italy

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

The prediction of human eye fixations has been recently gaining a lot of attention thanks to the improvements shown by deep architectures. In our work, we go beyond classical feed-forward networks to predict saliency maps and propose a Saliency Attentive Model which incorporates neural attention mechanisms to iteratively refine predictions. Experiments demonstrate that the proposed strategy overcomes by a considerable margin the state of the art on the largest dataset available for saliency prediction. Here, we provide experimental results on other popular saliency datasets to confirm the effectiveness and the generalization capabilities of our model, which enable us to reach the state of the art on all considered datasets.

关键词： Predictive models Visualization Measurement Feature extraction conferences computer architecture Computational modeling

来源：评论

学校读者我要写书评

暂无评论

Zero-shot Learning Using Multimodal Descriptions

Zero-shot Learning Using Multimodal Descriptions

引用

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

作者： Mall, Utkarsh Hariharan, Bharath Bala, Kavita Cornell Univ Ithaca NY 14853 USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Zero-shot learning (ZSL) tackles the problem of recognizing unseen classes using only semantic descriptions, e.g., attributes. Current zero-shot learning techniques all assume that a single vector of attributes suffices to describe each category. We show that this assumption is incorrect. Many classes in real world problems have multiple modes of appearance: male and female birds vary in appearance, for instance. Domain experts know this and can provide attribute descriptions of the chief modes of appearance for each class. Motivated by this, we propose the task of multi-modal zero-shot learning, where the learner must learn from these multimodal attribute descriptions. We present a technique for addressing this problem of multimodal ZSL that outperforms the unimodal counterpart significantly. We posit that multimodal ZSL is more practical for real-world problems where complex intra-class variation is common.

关键词： computer vision conferences Computational modeling Semantics Manuals Benchmark testing Birds

来源：评论

学校读者我要写书评

暂无评论

Stargazer: A Transformer-based Driver Action Detection System for Intelligent Transportation

Stargazer: A Transformer-based Driver Action Detection Syste...

引用

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

作者： Liang, Junwei Zhu, He Zhang, Enwei Zhang, Jun Tencent Youtu Lab Shenzhen Peoples R China Tsinghua Univ Beijing Peoples R China

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Distracted driver actions can be dangerous and cause severe accidents. Thus, it is important to detect and eliminate distracted driving behaviors on the road to save lives. To this end, we study driver action detection using videos captured inside the vehicle. We propose Stargazer, an efficient, transformer-based system exploiting rich temporal features about the human behavioral information, with a simple yet effective action temporal localization framework. The core of our system contains an improved version of the multi-scale vision transformer network, which learns a hierarchy of robust representations. We then use a slidingwindow classification strategy to facilitate temporal localization of actions-of-interest. The proposed system wins the second place in the Naturalistic Driving Action recognition of AI City Challenge 2022 (Track 3)(1). The code and models are released(2).

关键词： Location awareness Roads Urban areas Transformer cores Transformers pattern recognition Behavioral sciences

来源：评论

学校读者我要写书评

暂无评论

Reconstructing Spectral Images from RGB-Images using a Convolutional Neural Network 31

Reconstructing Spectral Images from RGB-Images using a Convo...

引用

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

作者： Stiebel, Tarek Koppers, Simon Seltsam, Philipp Merhof, Dorit Rhein Westfal TH Aachen Inst Imaging & Comp Vis Aachen Germany

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Recovering high-dimensional spectral images taken with spectrally low-dimensional camera systems, in the extreme case RGB-images, has been of great interest for a variety of applications. An accurate spectral reconstruction is typically required to either achieve a better color accuracy or to improve object recognition/classification tasks. Almost all published work to date aims at performing a mapping from individual camera signals towards the corresponding spectrum. However, it might be beneficial to consider not only single pixels, but also contextual information. Here, we propose a convolutional neural network architecture that learns a mapping from RGB- to spectral images. We trained the network on the largest hyper-spectral data set available to date [;'I and analyzed the influence of different error metrics as loss functions. An objective evaluation of the performance in comparison to state of the art spectral reconstruction techniques is given by participating in the NTIRE 2018 challenge on spectral reconstruction [1].

关键词： computer vision pattern recognition conferences

来源：评论

学校读者我要写书评

暂无评论

Large-Scale Ecological Analyses of Animals in the Wild using computer vision 31

Large-Scale Ecological Analyses of Animals in the Wild using...

引用

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

作者： Timm, Mikayla Maji, Subhransu Fuller, Todd Univ Massachusetts Amherst MA 01003 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Camera traps are increasingly being deployed by ecologists and citizen-scientists as a cost-effective way of obtaining large amounts of animal images in the wild. In order to analyze this data, the images are labeled manually by ecologists, where they identify species of animals and more fine-grained details, such as animal sex or age, or even individual animal identities. However, with the number of camera trap images quickly outgrowing the capacity of the labelers, ecologists are unable to keep up with the wealth of data they are obtaining. Using computer vision, we can automatically generate labels for new camera trap images at the rate that they are being obtained, allowing ecologists to uncover ecological and biological information at a scale previously not possible. In this paper, we explore computer vision approaches for species identification in camera trap images and for individual jaguar identification, both of which show promising results. We make this novel dataset publicly available for future research directions and further exploration.

关键词： Animals Cameras Training computer vision Biological system modeling Task analysis Semantics

来源：评论

学校读者我要写书评

暂无评论

Dressing in Order: Recurrent Person Image Generation for Pose Transfer, Virtual Try-on and Outfit Editing

Dressing in Order: Recurrent Person Image Generation for Pos...

引用

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

作者： Cui, Aiyu McKee, Daniel Lazebnik, Svetlana Univ Illinois Champaign IL 61820 USA

ISBN: (纸本)9781665448994

We propose a flexible person generation framework called Dressing in Order (DiOr), which supports 2D pose transfer, virtual try-on, and several fashion editing tasks. The key to DiOr is a novel recurrent generation pipeline to sequentially put garments on a person, so that trying on the same garments in different orders will result in different looks. Our system can produce dressing effects not achievable by existing work, including different interactions of garments (e.g., wearing a top tucked into the bottom or over it), as well as layering of multiple garments of the same type (e.g., jacket over shirt over t-shirt). DiOr explicitly encodes the shape and texture of each garment, enabling these elements to be edited separately. Extensive evaluations show that DiOr outperforms other recent methods like ADGAN [18] in terms of output quality, and handles a wide range of editing functions for which there is no direct supervision.

关键词： computer vision Shape Image synthesis conferences Clothing Pipelines pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Parallel Generative Adversarial Network for Third-person to First-person Image Generation

Parallel Generative Adversarial Network for Third-person to ...

引用

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

作者： Liu, Gaowen Latapie, Hugo Kilic, Ozkan Lawrence, Adam Cisco Res Emerging Technol & Incubat San Jose CA 95134 USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Cross-view image generation has been recently proposed to generate images of one view from another dramatically different view. In this paper, we investigate third-person (exocentric) view to first-person (egocentric) view image generation. This is a challenging task since egocentric view sometimes is remarkably different from exocentric view. Thus, transforming the appearances across the two views is a non-trivial task. To this end, we propose a novel Parallel Generative Adversarial Network (P-GAN) with a novel cross-cycle loss to learn the shared information for generating egocentric images from exocentric view. We also incorporate a novel contextual feature loss in the learning procedure to capture the contextual information in images. Extensive experiments on the Exo-Ego datasets [5] show that our model outperforms the state-of-the-art approaches.

关键词： computer vision Image synthesis conferences Computational modeling Generative adversarial networks pattern recognition Task analysis

来源：评论

学校读者我要写书评

暂无评论

Sample-free white-box out-of-distribution detection for deep learning

Sample-free white-box out-of-distribution detection for deep...

引用

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

作者： Begon, Jean-Michel Geurts, Pierre Univ Liege Liege Belgium

ISBN: (纸本)9781665448994

Being able to detect irrelevant test examples with respect to deployed deep learning models is paramount to properly and safely using them. In this paper, we address the problem of rejecting such out-of-distribution (OOD) samples in a fully sample-free way, i.e., without requiring any access to in-distribution or OOD samples. We propose several indicators which can be computed alongside the prediction with little additional cost, assuming white-box access to the network. These indicators prove useful, stable and complementary for OOD detection on frequently-used architectures. We also introduce a surprisingly simple, yet effective summary OOD indicator. This indicator is shown to perform well across several networks and datasets and can furthermore be easily tuned as soon as samples become available. Lastly, we discuss how to exploit this summary in real-world settings.

关键词： Deep learning computer vision Filtering Computational modeling conferences computer architecture Data models

来源：评论

学校读者我要写书评

暂无评论

Boundary-aware Image Inpainting with Multiple Auxiliary Cues

Boundary-aware Image Inpainting with Multiple Auxiliary Cues

引用

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

作者： Yamashita, Yohei Shimosato, Kodai Ukita, Norimichi Toyota Technol Inst Nagoya Japan

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Image inpainting (a.k.a. image completion) allows us to remove unexpected foreground objects from an observed image and to restore the removed region with background pixels. The performance of image inpainting is improved by auxiliary cues such as edge boundaries and segmentation regions. As a new auxiliary cue, this paper focuses on a depth image that is estimated from an input RGB image by monocular depth estimation. In the depth image, boundaries between different objects (e.g., objects located in different distances) with similar pixel values might be available, while those boundaries are difficult to be detected by edge detection and segmentation. Our proposed method employs those boundaries in the edge and depth images as auxiliary cues. Experiments demonstrate that our proposed method augmented by the depth image outperforms its baseline quantitatively (i.e., 1.17dB and 0.74dB PSNR gains on the Paris-StreetView and Places datasets, respectively) and qualitatively.

关键词： Image segmentation computer vision Image edge detection conferences Estimation pattern recognition Image restoration

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 << < 29 30 31 32 33 34 35 36 37 38 > >>

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：