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

6,506 篇 会议
29 篇 期刊文献
10 册 图书

馆藏范围

6,544 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

3,906 篇 工学
- 3,683 篇 计算机科学与技术...
- 1,504 篇 软件工程
- 802 篇 光学工程
- 359 篇 信息与通信工程
- 256 篇 控制科学与工程
- 204 篇 机械工程
- 176 篇 电气工程
- 95 篇 生物医学工程（可授...
- 79 篇 生物工程
- 77 篇 电子科学与技术（可...
- 61 篇 仪器科学与技术
- 38 篇 建筑学
- 36 篇 力学（可授工学、理...
- 34 篇 土木工程
- 31 篇 航空宇航科学与技...
- 31 篇 安全科学与工程
- 22 篇 材料科学与工程（可...
- 22 篇 交通运输工程
1,537 篇 理学
- 980 篇 物理学
- 960 篇 数学
- 376 篇 统计学（可授理学、...
- 152 篇 生物学
- 34 篇 系统科学
- 24 篇 化学
168 篇 管理学
- 120 篇 图书情报与档案管...
- 50 篇 管理科学与工程(可...
- 33 篇 工商管理
139 篇 医学
- 138 篇 临床医学
- 21 篇 基础医学(可授医学...
20 篇 法学
- 19 篇 社会学
11 篇 农学
10 篇 教育学
7 篇 经济学
3 篇 军事学
3 篇 艺术学

主题

2,304 篇 computer vision
871 篇 pattern recognit...
640 篇 cameras
634 篇 computer science
577 篇 face recognition
553 篇 layout
523 篇 image segmentati...
509 篇 conferences
503 篇 shape
450 篇 robustness
438 篇 object recogniti...
390 篇 humans
341 篇 feature extracti...
318 篇 training
307 篇 object detection
261 篇 application soft...
259 篇 image recognitio...
250 篇 lighting
239 篇 image reconstruc...
237 篇 computational mo...

机构

44 篇 microsoft resear...
26 篇 department of co...
21 篇 swiss fed inst t...
21 篇 school of comput...
20 篇 department of co...
19 篇 swiss fed inst t...
19 篇 carnegie mellon ...
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 school of comput...
14 篇 school of comput...
13 篇 univ maryland co...
13 篇 microsoft resear...
13 篇 microsoft resear...

作者

39 篇 timofte radu
28 篇 s.k. nayar
25 篇 xiaoou tang
25 篇 huang thomas s.
22 篇 t. kanade
20 篇 t.s. huang
19 篇 van gool luc
19 篇 t. darrell
19 篇 chellappa rama
18 篇 nayar shree k.
17 篇 a.k. jain
17 篇 a. zisserman
17 篇 jain anil k.
17 篇 zisserman andrew
16 篇 g. healey
16 篇 torralba antonio
16 篇 heung-yeung shum
16 篇 l. van gool
15 篇 zhang lei
15 篇 li stan z.

语言

6,544 篇 英文
1 篇 其他

检索条件"任意字段=2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005"

共 6545 条记录，以下是241-250 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：

PAND: Precise Action recognition on Naturalistic Driving

PAND: Precise Action Recognition on Naturalistic Driving

引用

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

作者： Zhao, Hangyue Xiao, Yuchao Zhao, Yanyun Beijing Univ Posts & Telecommun Beijing Peoples R China Beijing Key Lab Network Syst & Network Culture Beijing Peoples R China

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Temporal action localization for untrimmed videos is a difficult problem in computer vision. It is challenge to infer the start and end of activity instances on small-scale datasets covering multi-view information accurately. In this paper, we propose an effective activity temporal localization and classification method to localize the temporal boundaries and predict the class label of activities for naturalistic driving. Our approach includes (i) a distraction behavior recognition and localization method in naturalistic driving videos on small-scale data sets, (ii) a strategy that uses multi-branch network to make full use of information from different channels, (iii)a post-processing method for selecting and correcting temporal range to ensure that our system finds accurate boundaries. In addition, the frame-level object detection information is also utilized. Extensive experiments prove the effectiveness of our method and we rank the 6th on the Test-A2 of the 6th AI City Challenge track 3.

关键词： Location awareness computer vision Urban areas Pipelines Object detection Data models pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Generalized Category Discovery

Generalized Category Discovery

引用

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

作者： Vaze, Sagar Hant, Kai Vedaldi, Andrea Zisserman, Andrew Univ Oxford Dept Engn Sci Visual Geometry Grp Oxford England Univ Hong Kong Hong Kong Peoples R China

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

In this paper, we consider a highly general image recognition setting wherein, given a labelled and unlabelled set of images, the task is to categorize all images in the unlabelled set. Here, the unlabelled images may come from labelled classes or from novel ones. Existing recognition methods are not able to deal with this setting, because they make several restrictive assumptions, such as the unlabelled instances only coming from known - or unknown - classes, and the number of unknown classes being known a-priori. We address the more unconstrained setting, naming it `Generalized Category Discovery', and challenge all these assumptions. We first establish strong baselines by taking state-of-the-art algorithms from novel category discovery and adapting them for this task. Next, we propose the use of vision transformers with contrastive representation learning for this open-world setting. We then introduce a simple yet effective semi-supervised k-means method to cluster the unlabelled data into seen and unseen classes automatically, substantially outperforming the baselines. Finally, we also propose a new approach to estimate the number of classes in the unlabelled data. We thoroughly evaluate our approach on public datasets for generic object classification and on fine-grained datasets, leveraging the recent Semantic Shift Benchmark suite. Code: https://***/similar to vgg/research/gcd

关键词： Representation learning computer vision Image recognition Limiting Codes Semantics Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

DRHDR: A Dual branch Residual Network for Multi-Bracket High Dynamic Range Imaging

DRHDR: A Dual branch Residual Network for Multi-Bracket High...

引用

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

作者： Marin-Vega, Juan Sloth, Michael Schneider-Kamp, Peter Rottger, Richard Univ Southern Denmark Dept Math & Comp Sci IMADA Odense Denmark Esoft Syst Odense Denmark

ISBN: (纸本)9781665487399

We introduce DRHDR, a Dual branch Residual Convolutional Neural Network for Multi-Bracket HDR Imaging. To address the challenges of fusing multiple brackets from dynamic scenes, we propose an efficient dual branch network that operates on two different resolutions. The full resolution branch uses a Deformable Convolutional Block to align features and retain high-frequency details. A low resolution branch with a Spatial Attention Block aims to attend wanted areas from the non-reference brackets, and suppress displaced features that could incur on ghosting artifacts. By using a dual branch approach we are able to achieve high quality results while constraining the computational resources required to estimate the HDR results.

关键词： computer vision conferences Imaging Dynamic range pattern recognition Complexity theory Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Multi-Class Cell Detection Using Modified Self-Attention

Multi-Class Cell Detection Using Modified Self-Attention

引用

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

作者： Sugimoto, Tatsuhiko Ito, Hiroaki Teramoto, Yuki Yoshizawa, Akihiko Bise, Ryoma Kyushu Univ Fukuoka Japan Kyoto Univ Hosp Kyoto Japan

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Multi-class cell detection (cancer or non-cancer) from a whole slide image (WSI) is an important task for pathological diagnosis. Cancer and non-cancer cells often have a similar appearance, so it is difficult even for experts to classify a cell from a patch image of individual cells. They usually identify the cell type not only on the basis of the appearance of a single cell but also on the context of the surrounding cells. For using such information, we propose a multi-class cell-detection method that introduces a modified self-attention to aggregate the surrounding image features of both classes. Experimental results demonstrate the effectiveness of the proposed method;our method achieved the best performance compared with a method, which simply uses the standard self-attention method.

关键词： Heating systems Pathology computer vision Aggregates conferences Feature extraction pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Generative Flows as a General Purpose Solution for Inverse Problems

Generative Flows as a General Purpose Solution for Inverse P...

引用

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

作者： Chavez, Jose A. San Pablo Catholic Univ Arequipa Peru

ISBN: (纸本)9781665487399

Due to the success of generative flows to model data distributions, they have been explored in inverse problems. Given a pre-trained generative flow, previous work proposed to minimize the 2-norm of the latent variables as a regularization term. The intuition behind it was to ensure high likelihood latent variables that produce the closest restoration. However, high-likelihood latent variables may generate unrealistic samples as we show in our experiments. We therefore propose a solver to directly produce high-likelihood reconstructions. We hypothesize that our approach could make generative flows a general purpose solver for inverse problems. Furthermore, we propose 1x1 coupling functions to introduce permutations in a generative flow. It has the advantage that its inverse does not require to be calculated in the generation process. Finally, we evaluate our method for denoising, deblurring, inpainting, and colorization. We observe a compelling improvement of our method over prior works.

关键词： Couplings computer vision Inverse problems conferences Noise reduction Data models pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Medusa: Universal Feature Learning via Attentional Multitasking

Medusa: Universal Feature Learning via Attentional Multitask...

引用

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

作者： Spencer, Jaime Bowden, Richard Hadfield, Simon Univ Surrey Ctr Vis Speech & Signal Proc CVSSP Guildford Surrey England

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Recent approaches to multi-task learning (MTL) have focused on modelling connections between tasks at the decoder level. This leads to a tight coupling between tasks, which need retraining if a new task is inserted or removed. We argue that MTL is a stepping stone towards universal feature learning (UFL), which is the ability to learn generic features that can be applied to new tasks without retraining. We propose Medusa to realize this goal, designing task heads with dual attention mechanisms. The shared feature attention masks relevant backbone features for each task, allowing it to learn a generic representation. Meanwhile, a novel Multi-Scale Attention head allows the network to better combine per-task features from different scales when making the final prediction. We show the effectiveness of Medusa in UFL (+13.18% improvement), while maintaining MTL performance and being 25% more efficient than previous approaches.

关键词： Representation learning Couplings computer vision conferences Multitasking pattern recognition Decoding

来源：评论

学校读者我要写书评

暂无评论

Artistic Style Novel View Synthesis Based on A Single Image

Artistic Style Novel View Synthesis Based on A Single Image

引用

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

作者： Tseng, Kuan-Wei Lee, Yao-Chih Chen, Chu-Song Natl Taiwan Univ Taipei Taiwan Tokyo Inst Technol Tokyo Japan

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Recent progress in 3D display technologies has raised the demand for stylized 3D digital content. Previous approaches either perform style transfer on stereoscopic image pairs or reconstruct 3D environment with multiple view images. In this paper, we propose a novel view stylization framework that can convert a single 2D image into multiple stylized views. It is a two-stage solution that contains view synthesis and neural style transfer. We estimate dense optical flow between the source and novel views so that the style transfer model can produce consistent results. Experimental results show that our method significantly improves the consistency among views compared to the baseline method.

关键词： computer vision Three-dimensional displays Stereo image processing conferences Computational modeling pattern recognition Optical flow

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

Neural Face Video Compression using Multiple Views

Neural Face Video Compression using Multiple Views

引用

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

作者： Volokitin, Anna Brugger, Stefan Benlalah, Ali Martin, Sebastian Amberg, Brian Tschannen, Michael Swiss Fed Inst Technol Zurich Switzerland Apple Cupertino CA USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Recent advances in deep generative models led to the development of neural face video compression codecs that use an order of magnitude less bandwidth than engineered codecs. These neural codecs reconstruct the current frame by warping a source frame and using a generative model to compensate for imperfections in the warped source frame. Thereby, the warp is encoded and transmitted using a small number of keypoints rather than a dense flow field, which leads to massive savings compared to traditional codecs. However, by relying on a single source frame only, these methods lead to inaccurate reconstructions (e.g. one side of the head becomes unoccluded when turning the head and has to be synthesized). Here, we aim to tackle this issue by relying on multiple source frames (views of the face) and present encouraging results.

关键词： Codecs Uncertainty Computational modeling Face recognition Video compression Streaming media Real-time systems

来源：评论

学校读者我要写书评

暂无评论

Domain Adaptable Normalization for Semi-Supervised Action recognition in the Dark

Domain Adaptable Normalization for Semi-Supervised Action Re...

引用

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

作者： Liang, Zixi Chen, Jiajun Chen, Rui Zheng, Bingbing Zhou, Mingyue Gao, Huaien Lin, Shan Guangzhou Xi Ma Informat Technol Co Guangzhou Peoples R China

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Action recognition in the dark is gaining more and more attention with the rapid development of intelligent recognition applications in real-world applications, e.g. self-driving at night and night surveillance. However, limited by the expensive labeling cost, it is impractical to produce a large-scale labeled dataset only for dark environments. Therefore, a practical solution adopted is to transfer models trained from clear environments to dark environments through semi-supervised learning. However, prior works rely heavily on additional efforts such as extra annotations, or extra sensors. To this end, we proposed a novel and simple Domain Adaptable Normalization (DANorm) method to align different domains directly, which consists of feature normalization, angle constraint and the Pseudo-Label. Specifically, the proposed DANorm method enables the model automatically learning the associated features between labeled source domain and unlabeled target domain by constraining the feature subspace vectors. Experimental results show that our model achieves superiority performance on Semi-supervised ARID dataset.

关键词： Adaptation models computer vision Costs Surveillance conferences Semisupervised learning pattern 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 << < 21 22 23 24 25 26 27 28 29 30 > >>

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：