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441-450 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 learning for audio applications: A computer vision approach

Semantic learning for audio applications: A computer vision ...

引用

2006 conference on computer vision and pattern recognition workshops

作者： Sukthankar, Rahul Ke, Yan Hoiem, Derek Intel Research Pittsburgh School of Computer Science Carnegie Mellon

ISBN: (纸本)0769526462

Recent work in machine learning has significantly benefited semantic extraction tasks in computer vision, particularly for object recognition and image retrieval. We argue that the computer vision techniques that have been successfully applied in those settings can effectively be translated to other domains, such as audio. This claim is supported by recent results in music vs. speech classification, structure from sound, robust music identification and sound object recognition. This paper focuses on two such audio applications and demonstrates how ideas from computer vision map naturally to these problems. © 2006 IEEE.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

Editing like Humans: A Contextual, Multimodal Framework for Automated Video Editing

Editing like Humans: A Contextual, Multimodal Framework for ...

引用

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

作者： Koorathota, Sharath Adelman, Patrick Cotton, Kelly Sajda, Paul Columbia Univ Dept Biomed Engn New York NY 10027 USA Fovea Inc New York NY 10001 USA CUNY Grad Ctr Dept Psychol New York NY USA

ISBN: (纸本)9781665448994

We propose an automated video editing model, which we term contextual and multimodal video editing (CMVE). The model leverages visual and textual metadata describing videos, integrating essential information from both modalities, and uses a learned editing style from a single example video to coherently combine clips. The editing model is useful for tasks such as generating news clip montages and highlight reels given a text query that describes the video storyline. The model exploits the perceptual similarity between video frames, objects in videos and text descriptions to emulate coherent video editing. Amazon Mechanical Turk participants made judgements comparing CMVE to expert human editing. Experimental results showed no significant difference in the CMVE vs human edited video in terms of matching the text query and the level of interest each generates, suggesting CMVE is able to effectively integrate semantic information across visual and textual modalities and create perceptually coherent quality videos typical of human video editors. We publicly release an online demonstration of our method.

关键词： Training Visualization computer vision conferences Semantics Metadata pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Fast and Robust Perspective Rectification of Document Images on a Smartphone

Fast and Robust Perspective Rectification of Document Images...

引用

27th IEEE conference on computer vision and pattern recognition (CVPR)

作者： Williem Simon, Christian Cho, Sungdae Park, In Kyu Inha Univ Dept Informat & Commun Engn Inchon 402751 South Korea Samsung Elect Co Ltd Div Mobile Commun Suwon 443742 South Korea

ISBN: (纸本)9781479943098

This paper presents a perspective rectification framework for mobile device that is fast and robust to recovering the fronto-parallel view of perspectively distorted document images. The conventional approaches is too heavy to be implemented on a mobile device. In addition, they fails to reject the false case of the perspective rectification. To ameliorate such problems, the proposed framework is designed to pursue a fast and robust algorithm to detect horizontal and vertical vanishing points efficiently and robustly. Then, perspective rectification is performed using both horizontal and vertical vanishing points. In addition, the proposed framework has an adaptive scheme to detect the false case of the perspective rectification and skip the procedure without using the vertical vanishing point. Note that, the proposed framework is designed for consumer application so that bad results are rejected before they are shown for users. We demonstrate the performance of the proposed framework on various challenging examples to confirm that the proposed system is fast and robust in rectifying the perspectively distorted images.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

The Effect of Improving Annotation Quality on Object Detection Datasets: A Preliminary Study

The Effect of Improving Annotation Quality on Object Detecti...

引用

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

作者： Ma, Jiaxin Ushiku, Yoshitaka Sagara, Miori OMRON SINIC X Corp Tokyo Japan Baobab Inc Tokyo Japan

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

In this study, we partially reannotate conventional benchmark datasets for object detection and check whether there is performance improvement/drop compared with the original annotations. Recent studies on the annotation qualities of ImageNet for image classification revealed some issues of how to associate only a single label to each image accurately. Object detection, on the other hand, should have other nontrivial issues because there are multiple objects in a single image, and realizing consistency among bounding boxes is challenging. A team of professional annotators was formed for MS COCO and Google Open Images datasets. To realize highly-consistent annotations, we prepared carefully designed guidelines for each category and selected quality inspectors who checked the annotation quality of each annotator. Finally, we applied conventional object detection methods for reannotated parts of each dataset. We found mixed results: whether the performance dropped or improved depended on each category and dataset.

关键词： Annotations conferences Object detection Machine learning Benchmark testing Internet pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Unsupervised Detection of Cancerous Regions in Histology Imagery using Image-to-Image Translation

Unsupervised Detection of Cancerous Regions in Histology Ima...

引用

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

作者： Stepec, Dejan Skocaj, Danijel Univ Ljubljana Fac Comp & Informat Sci Vecna Pot 113 Ljubljana 1000 Slovenia XLAB Doo Pot Za Brdom 100 Ljubljana 1000 Slovenia

ISBN: (纸本)9781665448994

Detection of visual anomalies refers to the problem of finding patterns in different imaging data that do not conform to the expected visual appearance and is a widely studied problem in different domains. Due to the nature of anomaly occurrences and underlying generating processes, it is hard to characterize them and obtain labeled data. Obtaining labeled data is especially difficult in biomedical applications, where only trained domain experts can provide labels, which often come in large diversity and complexity. Recently presented approaches for unsupervised detection of visual anomalies approaches omit the need for labeled data and demonstrate promising results in domains, where anomalous samples significantly deviate from the normal appearance. Despite promising results, the performance of such approaches still lags behind supervised approaches and does not provide a one-fits-all solution. In this work, we present an image-to-image translation-based framework that significantly surpasses the performance of existing unsupervised methods and approaches the performance of supervised methods in a challenging domain of cancerous region detection in histology imagery.

关键词： Visualization computer vision Image analysis Histopathology conferences Biomedical measurement pattern recognition

来源：评论

学校读者我要写书评

暂无评论

BGT-Net: Bidirectional GRU Transformer Network for Scene Graph Generation

BGT-Net: Bidirectional GRU Transformer Network for Scene Gra...

引用

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

作者： Dhingra, Naina Ritter, Florian Kunz, Andreas Swiss Fed Inst Technol Innovat Ctr Virtual Real Zurich Switzerland

ISBN: (纸本)9781665448994

Scene graphs are nodes and edges consisting of objects and object-object relationships, respectively. Scene graph generation (SGG) aims to identify the objects and their relationships. We propose a bidirectional GRU (BiGRU) transformer network (BGT-Net) for the scene graph generation for images. This model implements novel object-object communication to enhance the object information using a BiGRU layer. Thus, the information of all objects in the image is available for the other objects, which can be leveraged later in the object prediction step. This object information is used in a transformer encoder to predict the object class as well as to create object-specific edge information via the use of another transformer encoder. To handle the dataset bias induced by the long-tailed relationship distribution, softening with a log-softmax function and adding a bias adaptation term to regulate the bias for every relation prediction individually showed to be an effective approach. We conducted an elaborate study on experiments and ablations using open-source datasets, i.e., Visual Genome, Open-Images, and Visual Relationship Detection datasets, demonstrating the effectiveness of the proposed model over state of the art.

关键词： Visualization computer vision Image edge detection conferences Genomics pattern recognition Softening

来源：评论

学校读者我要写书评

暂无评论

PseudoProp: Robust Pseudo-Label Generation for Semi-Supervised Object Detection in Autonomous Driving Systems

PseudoProp: Robust Pseudo-Label Generation for Semi-Supervis...

引用

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

作者： Hu, Shu Liu, Chun-Hao Dutta, Jayanta Chang, Ming-Ching Lyu, Siwei Ramakrishnan, Naveen Univ Buffalo SUNY Buffalo NY USA Bosch Ctr Artificial Intelligence Sunnyvale CA 94085 USA SUNY Albany Albany NY 12222 USA Amazon Seattle WA USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Semi-supervised object detection methods are widely used in autonomous driving systems, where only a fraction of objects are labeled. To propagate information from the labeled objects to the unlabeled ones, pseudo-labels for unlabeled objects must be generated. Although pseudo-labels have proven to improve the performance of semisupervised object detection significantly, the applications of image-based methods to video frames result in numerous miss or false detections using such generated pseudo-labels. In this paper, we propose a new approach, PseudoProp, to generate robust pseudo-labels by leveraging motion continuity in video frames. Specifically, PseudoProp uses a novel bidirectional pseudo-label propagation approach to compensate for misdetection. A feature-based fusion technique is also used to suppress inference noise. Extensive experiments on the large-scale Cityscapes dataset demonstrate that our method outperforms the state-of-the-art semi-supervised object detection methods by 7.4% on mAP(75).

关键词： Training computer vision conferences Object detection Predictive models Feature extraction pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Wearable ImageNet: Synthesizing Tileable Textures via Dataset Distillation

Wearable ImageNet: Synthesizing Tileable Textures via Datase...

引用

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

作者： Cazenavette, George Wang, Tongzhou Torralba, Antonio Efros, Alexei A. Zhu, Jun-Yan Carnegie Mellon Univ Pittsburgh PA 15213 USA MIT Cambridge MA 02139 USA Univ Calif Berkeley Berkeley CA USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Recent methods for Dataset Distillation are able to take in a large set of images of a specific class (e.g., from ImageNet) and synthesize a single image, such that a classifier trained on that image could perform similarly to one trained on the original dataset. It was noticed that the resulting "distilled images" are often quite visually pleasing. In this paper, we describe a simple method for generating tileable distilled textures by sampling random crops from a toroidal canvas of synthetic pixels while enforcing that all such crops serve as effective distilled training data. Such distilled textures not only summarize a given image category in a visually interesting way, but also allow for generation of infinite texture patterns suitable for printing on fabric, clothing, etc. This paper might be just the first step in making the ImageNet dataset into a fashion statement.

关键词： Printing computer vision Wearable computers conferences Clothing Crops Training data

来源：评论

学校读者我要写书评

暂无评论

An End-to-End vision Transformer Approach for Image Copy Detection

An End-to-End Vision Transformer Approach for Image Copy Det...

引用

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

作者： Lee, Jiahe Steven Hsu, Wynne Lee, Mong Li Natl Univ Singapore Inst Data Sci Singapore Singapore Natl Univ Singapore Ctr Trusted Internet & Community Singapore Singapore

ISBN: (纸本)9798350365474

Image copy detection is one of the pivotal tools to safeguard online information integrity. The challenge lies in determining whether a query image is an edited copy, which necessitates the identification of candidate source images through a retrieval process. The process requires discriminative features comprising of both global descriptors that are designed to be augmentation-invariant and local descriptors that can capture salient foreground objects to assess whether a query image is an edited copy of some source reference image. This work describes an end-to-end solution that leverage a vision Transformer model to learn such discriminative features and perform implicit matching between the query image and the reference image. Experimental results on two benchmark datasets demonstrate that the proposed solution outperforms state-of-the-art methods. Case studies illustrate the effectiveness of our approach in matching reference images from which the query images have been copy-edited.

关键词： image copy detection image retrieval

来源：评论

学校读者我要写书评

暂无评论

BalaGAN: Cross-Modal Image Translation Between Imbalanced Domains

BalaGAN: Cross-Modal Image Translation Between Imbalanced Do...

引用

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

作者： Patashnik, Or Danon, Dov Zhang, Hao Cohen-Or, Daniel Tel Aviv Univ Tel Aviv Israel Simon Fraser Univ Burnaby BC Canada

ISBN: (纸本)9781665448994

State-of-the-art image translation methods tend to struggle in an imbalanced domain setting, where one image domain lacks richness and diversity. We introduce a new unsupervised translation network, BalaGAN, specifically designed to tackle the domain imbalance problem. We leverage the latent modalities of the richer domain to turn the image-to-image translation problem, between two imbalanced domains, into a multi-class translation problem, more resembling the style transfer setting. Specifically, we analyze the source domain and learn a decomposition of it into a set of latent modes or classes, without any supervision. This leaves us with a multitude of balanced crossdomain translation tasks, between all pairs of classes, including the target domain. During inference, the trained network takes as input a source image, as well as a reference style image from one of the modes as a condition, and produces an image which resembles the source on the pixel-wise level, but shares the same mode as the reference. We show that employing modalities within the dataset improves the quality of the translated images, and that BalaGAN outperforms strong baselines of both unconditioned and style-transfer-based image-to-image translation methods, in terms of image quality and diversity.

关键词： Training Image quality computer vision conferences pattern recognition Task analysis

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 << < 41 42 43 44 45 46 47 48 49 50 > >>

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：