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

3,915 篇 会议
2 篇 期刊文献

馆藏范围

3,917 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

3,011 篇 工学
- 2,919 篇 计算机科学与技术...
- 216 篇 软件工程
- 141 篇 机械工程
- 133 篇 光学工程
- 42 篇 生物工程
- 28 篇 信息与通信工程
- 25 篇 电气工程
- 17 篇 控制科学与工程
- 9 篇 电子科学与技术（可...
- 9 篇 化学工程与技术
- 9 篇 交通运输工程
- 8 篇 生物医学工程（可授...
- 7 篇 安全科学与工程
- 4 篇 材料科学与工程（可...
- 4 篇 建筑学
- 3 篇 土木工程
- 3 篇 农业工程
1,559 篇 医学
- 1,558 篇 临床医学
- 3 篇 基础医学(可授医学...
174 篇 理学
- 136 篇 物理学
- 43 篇 生物学
- 29 篇 数学
- 16 篇 统计学（可授理学、...
- 10 篇 化学
14 篇 管理学
- 7 篇 管理科学与工程(可...
- 7 篇 图书情报与档案管...
- 3 篇 工商管理
5 篇 法学
- 3 篇 社会学
- 2 篇 法学
2 篇 教育学
- 2 篇 教育学
2 篇 农学
1 篇 经济学

主题

2,408 篇 computer vision
1,085 篇 training
1,043 篇 pattern recognit...
805 篇 conferences
709 篇 computational mo...
543 篇 visualization
491 篇 computer archite...
446 篇 three-dimensiona...
410 篇 semantics
409 篇 benchmark testin...
383 篇 codes
331 篇 transformers
290 篇 deep learning
277 篇 feature extracti...
260 篇 neural networks
256 篇 task analysis
238 篇 shape
216 篇 image segmentati...
204 篇 measurement
202 篇 object detection

机构

72 篇 tsinghua univ pe...
59 篇 univ sci & techn...
55 篇 zhejiang univ pe...
55 篇 chinese univ hon...
51 篇 carnegie mellon ...
51 篇 peng cheng lab p...
49 篇 swiss fed inst t...
47 篇 sensetime res pe...
46 篇 shanghai ai lab ...
42 篇 univ hong kong p...
38 篇 huawei noahs ark...
35 篇 univ chinese aca...
35 篇 shanghai jiao to...
33 篇 alibaba grp peop...
32 篇 tech univ munich...
31 篇 stanford univ st...
30 篇 peking univ peop...
30 篇 swiss fed inst t...
29 篇 adobe res san jo...
29 篇 google res mount...

作者

63 篇 timofte radu
30 篇 van gool luc
19 篇 yang yi
19 篇 qiao yu
18 篇 loy chen change
16 篇 zhang lei
16 篇 radu timofte
15 篇 sun jian
14 篇 liu yang
14 篇 liu shuaicheng
14 篇 tao dacheng
13 篇 li xin
13 篇 fan haoqiang
13 篇 chen wei-ting
12 篇 luo ping
12 篇 chen dongdong
12 篇 wang kai
12 篇 wang xinchao
12 篇 torralba antonio
12 篇 ghanem bernard

语言

3,916 篇 英文
1 篇 其他

检索条件"任意字段=2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022"

共 3917 条记录，以下是121-130 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：

Deep-FlexISP: A Three-Stage Framework for Night Photography Rendering

Deep-FlexISP: A Three-Stage Framework for Night Photography ...

引用

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

作者： Liu, Shuai Feng, Chaoyu Wang, Xiaotao Wang, Hao Zhu, Ran Li, Yongqiang Lei, Lei Xiaomi Inc Shanghai Peoples R China

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Night photography rendering is challenging due to images' high noise level, less vivid color, and low dynamic range. In this work, we propose a three-stage cascade framework named Deep-FlexISP, which decomposes the ISP into three weakly correlated sub-tasks: raw image denoising, white balance, and Bayer to sRGB mapping, for the following considerations. First, task decomposition can enhance the learning ability of the framework and make it easier to converge. Second, weak correlation sub-tasks do not influence each other too much, so the framework has a high degree of freedom. Finally, noise, color, and brightness are essential for night photographs. Our framework can flexibly adjust different styles according to personal preferences with the vital learning ability and the degree of freedom. Compared with the other Deep-ISP methods, our proposed Deep-FlexISP shows state-of-the-art performance and achieves first place in people's choice and photographer's choice in NTIRE 2022 Night Photography Render Challenge.

关键词： Photography Image color analysis Brightness Noise reduction Rendering (computer graphics) pattern recognition Task analysis

来源：评论

学校读者我要写书评

暂无评论

Self-supervised vision Transformers for Land-cover Segmentation and Classification

Self-supervised Vision Transformers for Land-cover Segmentat...

引用

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

作者： Scheibenreif, Linus Hanna, Joelle Mommert, Michael Borth, Damian Univ St Gallen AIML Lab Sch Comp Sci Rosenbergstr 30 St Gallen Switzerland

ISBN: (纸本)9781665487399

Transformer models have recently approached or even surpassed the performance of ConvNets on computer vision tasks like classification and segmentation. To a large degree, these successes have been enabled by the use of large-scale labelled image datasets for supervised pre-training. This poses a significant challenge for the adaption of vision Transformers to domains where datasets with millions of labelled samples are not available. In this work, we bridge the gap between ConvNets and Transformers for Earth observation by self-supervised pre-training on large-scale unlabelled remote sensing data(1). We show that self-supervised pre-training yields latent task-agnostic representations that can be utilized for both land cover classification and segmentation tasks, where they significantly outperform the fully supervised baselines. Additionally, we find that subsequent fine-tuning of Transformers for specific downstream tasks performs on-par with commonly used ConvNet architectures. An ablation study further illustrates that the labelled dataset size can be reduced to one-tenth after self-supervised pre-training while still maintaining the performance of the fully supervised approach.

关键词： Training Earth computer vision Image segmentation Computational modeling conferences Transformers

来源：评论

学校读者我要写书评

暂无评论

An Attention-based Method for Multi-label Facial Action Unit Detection

An Attention-based Method for Multi-label Facial Action Unit...

引用

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

作者： Le Hoai, Duy Lim, Eunchae Choi, Eunbin Kim, Sieun Pant, Sudarshan Lee, Guee-Sang Kim, Soo-Huyng Yang, Hyung-Jeong Chonnam Natl Univ Gwangju South Korea

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Facial Action Coding System is an approach for modeling the complexity of human emotional expression. Automatic action unit (AU) detection is a crucial research area in human-computer interaction. This paper describes our submission to the third Affective Behavior Analysis in-the-wild (ABAW) competition 2022. We proposed a method for detecting facial action units in the video. In the first stage, a lightweight CNN-based feature extractor is employed to extract the feature map from each video frame. Then, an attention module is applied to refine the attention map. The attention encoded vector is derived using a weighted sum of the feature map and the attention scores later. Finally, the sigmoid function is used at the output layer to make the prediction suitable for multi-label AUs detection. We achieved a macro F1 score of 0.48 on the validation set and 0.4206 on the test set compared to 0.39 and 0.3650 from the ABAW challenge baseline model.

关键词： Human computer interaction Gold computer vision conferences Computational modeling Feature extraction Encoding

来源：评论

学校读者我要写书评

暂无评论

SPIN: Simplifying Polar Invariance for Neural networks Application to vision-based irradiance forecasting

SPIN: Simplifying Polar Invariance for Neural networks Appli...

引用

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

作者： Paletta, Quentin Hu, Anthony Arbod, Guillaume Blanc, Philippe Lasenby, Joan Univ Cambridge Cambridge England ENGIE Lab CRIGEN Stains France MINES ParisTech Paris France

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Translational invariance induced by pooling operations is an inherent property of convolutional neural networks, which facilitates numerous computer vision tasks such as classification. Yet to leverage rotational invariant tasks, convolutional architectures require specific rotational invariant layers or extensive data augmentation to learn from diverse rotated versions of a given spatial configuration. Unwrapping the image into its polar coordinates provides a more explicit representation to train a convolutional architecture as the rotational invariance becomes translational, hence the visually distinct but otherwise equivalent rotated versions of a given scene can be learnt from a single image. We show with two common vision-based solar irradiance forecasting challenges (i.e. using ground-taken sky images or satellite images), that this preprocessing step significantly improves prediction results by standardising the scene representation, while decreasing training time by a factor of 4 compared to augmenting data with rotations. In addition, this transformation magnifies the area surrounding the centre of the rotation, leading to more accurate short-term irradiance predictions.

关键词： Training computer vision Satellites Neural networks computer architecture Predictive models Cameras

来源：评论

学校读者我要写书评

暂无评论

Patch-wise Contrastive Style Learning for Instagram Filter Removal

Patch-wise Contrastive Style Learning for Instagram Filter R...

引用

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

作者： Kinli, Furkan Ozcan, Baris Kirac, Furkan Ozyegin Univ Vis & Graph Lab Video Istanbul Turkey

ISBN: (纸本)9781665487399

Image-level corruptions and perturbations degrade the performance of CNNs on different downstream vision tasks. Social media filters are one of the most common resources of various corruptions and perturbations for real-world visual analysis applications. The negative effects of these distractive factors can be alleviated by recovering the original images with their pure style for the inference of the downstream vision tasks. Assuming these filters substantially inject a piece of additional style information to the social media images, we can formulate the problem of recovering the original versions as a reverse style transfer problem. We introduce Contrastive Instagram Filter Removal Network (CIFR), which enhances this idea for Instagram filter removal by employing a novel multi-layer patch-wise contrastive style learning mechanism. Experiments show our proposed strategy produces better qualitative and quantitative results than the previous studies. Moreover, we present the results of our additional experiments for proposed architecture within different settings. Finally, we present the inference outputs and quantitative comparison of filtered and recovered images on localization and segmentation tasks to encourage the main motivation for this problem.

关键词： Training Matched filters Social networking (online) Perturbation methods Multimedia Web sites Semantics computer architecture

来源：评论

学校读者我要写书评

暂无评论

Out-Of-Distribution Detection In Unsupervised Continual Learning

Out-Of-Distribution Detection In Unsupervised Continual Lear...

引用

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

作者： He, Jiangpeng Zhu, Fengqing Purdue Univ Elmore Family Sch Elect & Comp Engn W Lafayette IN 47907 USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Unsupervised continual learning aims to learn new tasks incrementally without requiring human annotations. However, most existing methods, especially those targeted on image classification, only work in a simplified scenario by assuming all new data belong to new tasks, which is not realistic if the class labels are not provided. Therefore, to perform unsupervised continual learning in real life applications, an out-of-distribution detector is required at beginning to identify whether each new data corresponds to a new task or already learned tasks, which still remains under-explored yet. In this work, we formulate the problem for Out-of-distribution Detection in Unsupervised Continual Learning (OOD-UCL) with the corresponding evaluation protocol. In addition, we propose a novel OOD detection method by correcting the output bias at first and then enhancing the output confidence for in-distribution data based on task discriminativeness, which can be applied directly without modifying the learning procedures and objectives of continual learning. Our method is evaluated on CIFAR-100 dataset by following the proposed evaluation protocol and we show improved performance compared with existing OOD detection methods under the unsupervised continual learning scenario.

关键词： computer vision Protocols Annotations conferences Detectors pattern recognition Task analysis

来源：评论

学校读者我要写书评

暂无评论

SpiderNet: Hybrid Differentiable-Evolutionary Architecture Search via Train-Free Metrics

SpiderNet: Hybrid Differentiable-Evolutionary Architecture S...

引用

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

作者： Geada, Rob McGough, Andrew Stephen Red Hat Newcastle Upon Tyne Tyne & Wear England Newcastle Univ Newcastle Upon Tyne Tyne & Wear England

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Neural Architecture Search (NAS) algorithms are intended to remove the burden of manual neural network design, and have shown to be capable of designing excellent models for a variety of well-known problems. However, these algorithms require a variety of design parameters in the form of user configuration or hard-coded decisions which limit the variety of networks that can be discovered. This means that NAS algorithms do not eliminate model design tuning, they instead merely shift the burden of where that tuning needs to be applied. In this paper, we present SpiderNet, a hybrid differentiable-evolutionary and hardware-aware algorithm that rapidly and efficiently produces state-of-the-art networks. More importantly, SpiderNet is a proof-of-concept of a minimally-configured NAS algorithm;the majority of design choices seen in other algorithms are incorporated into SpiderNet's dynamically-evolving search space, minimizing the number of user choices to just two: reduction cell count and initial channel count. SpiderNet produces models highly-competitive with the state-of-the-art, and outperforms random search in accuracy, runtime, memory size, and parameter count.

关键词： Measurement Runtime Heuristic algorithms Microprocessors Neural networks computer architecture Manuals

来源：评论

学校读者我要写书评

暂无评论

When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search

When NAS Meets Trees: An Efficient Algorithm for Neural Arch...

引用

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

作者： Qian, Guocheng Zhang, Xuanyang Li, Guohao Zhao, Chen Chen, Yukang Zhang, Xiangyu Ghanem, Bernard Sun, Jian King Abdullah Univ Sci & Technol KAUST Thuwal Saudi Arabia MEGVII Technol Beijing Peoples R China Chinese Univ Hong Kong Hong Kong Peoples R China

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

The key challenge in neural architecture search (NAS) is designing how to explore wisely in the huge search space. We propose a new NAS method called TNAS (NAS with trees), which improves search efficiency by exploring only a small number of architectures while also achieving a higher search accuracy. TNAS introduces an architecture tree and a binary operation tree, to factorize the search space and substantially reduce the exploration size. TNAS performs a modified bi-level Breadth-First Search in the proposed trees to discover a high-performance architecture. Impressively, TNAS finds the global optimal architecture on CIFAR-10 with test accuracy of 94.37% in four GPU hours in NAS-Bench-201. The average test accuracy is 94.35%, which outperforms the state-of-the-art. Code is available at: https://***/guochengqian/TNAS.

关键词： computer vision Costs Codes conferences Graphics processing units computer architecture pattern recognition

来源：评论

学校读者我要写书评

暂无评论

A New Non-central Model for Fisheye Calibration

A New Non-central Model for Fisheye Calibration

引用

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

作者： Tezaur, Radka Kumar, Avinash Nestares, Oscar Intel Corp Santa Clara CA 95054 USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

A new non-central model suitable for calibrating fisheye cameras is proposed. It is a direct extension of the popular central model developed by Scaramuzza et al., used by Matlab computer vision Toolbox fisheye calibration tool. It allows adapting existing applications that are using this central model to a non-central projection that is more accurate, especially when objects captured in the images are close to the camera, and it makes it possible to switch easily between the more accurate non-central characterization of the fisheye camera and the more convenient central approximation, as needed. It is shown that the algorithms proposed by Scaramuzza et al. for their central model can be modified to accommodate the angle dependent axial viewpoint shift. This means, besides other, that a similar process can be used for calibration involving the viewpoint shift characterization and a user-friendly calibration tool can be produced with this new non-central model that does not require the user to provide detailed lens design specifications or an educated guess for the initial parameter values. Several other improvements to the Scaramuzza's central model are also introduced, helping to improve the performance of both the central model, and its non-central extension.

关键词： Adaptation models computer vision Three-dimensional displays Computational modeling Switches Cameras Mathematical models

来源：评论

学校读者我要写书评

暂无评论

Weakly-Supervised Action Detection Guided by Audio Narration

Weakly-Supervised Action Detection Guided by Audio Narration

引用

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

作者： Ye, Keren Kovashka, Adriana Cruise San Francisco CA 94107 USA Univ Pittsburgh Pittsburgh PA USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Videos are more well-organized curated data sources for visual concept learning than images. Unlike the 2-dimensional images which only involve the spatial information, the additional temporal dimension bridges and synchronizes multiple modalities. However, in most video detection benchmarks, these additional modalities are not fully utilized. For example, EPIC Kitchens is the largest dataset in first-person (egocentric) vision, yet it still relies on crowdsourced information to refine the action boundaries to provide instance-level action annotations. We explored how to eliminate the expensive annotations in video detection data which provide refined boundaries. We propose a model to learn from the narration supervision and utilize multimodal features, including RGB, motion flow, and ambient sound. Our model learns to attend to the frames related to the narration label while suppressing the irrelevant frames from being used. Our experiments show that noisy audio narration suffices to learn a good action detection model, thus reducing annotation expenses.

关键词： Visualization Annotations Soft sensors Refining Detectors pattern recognition Synchronization

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392页 << < 9 10 11 12 13 14 15 16 17 18 > >>

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：