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

8,901 篇 会议
43 篇 期刊文献
18 册 图书

馆藏范围

8,961 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

4,560 篇 工学
- 4,020 篇 计算机科学与技术...
- 2,178 篇 软件工程
- 1,241 篇 光学工程
- 555 篇 控制科学与工程
- 431 篇 信息与通信工程
- 430 篇 机械工程
- 294 篇 电气工程
- 287 篇 仪器科学与技术
- 179 篇 生物工程
- 159 篇 生物医学工程（可授...
- 119 篇 电子科学与技术（可...
- 61 篇 安全科学与工程
- 58 篇 建筑学
- 58 篇 化学工程与技术
- 52 篇 土木工程
- 49 篇 交通运输工程
- 40 篇 力学（可授工学、理...
2,065 篇 理学
- 1,382 篇 物理学
- 1,198 篇 数学
- 420 篇 统计学（可授理学、...
- 238 篇 生物学
- 54 篇 化学
- 36 篇 系统科学
263 篇 管理学
- 180 篇 图书情报与档案管...
- 89 篇 管理科学与工程(可...
- 47 篇 工商管理
223 篇 医学
- 222 篇 临床医学
- 39 篇 基础医学(可授医学...
205 篇 艺术学
- 205 篇 设计学（可授艺术学...
45 篇 法学
- 43 篇 社会学
21 篇 农学
14 篇 教育学
9 篇 经济学
6 篇 军事学

主题

3,412 篇 computer vision
1,216 篇 pattern recognit...
946 篇 cameras
908 篇 conferences
765 篇 computer science
674 篇 image segmentati...
618 篇 layout
598 篇 training
548 篇 shape
518 篇 robustness
451 篇 feature extracti...
448 篇 humans
445 篇 face recognition
405 篇 computational mo...
402 篇 object detection
365 篇 visualization
356 篇 computer archite...
336 篇 application soft...
304 篇 lighting
259 篇 image reconstruc...

机构

41 篇 microsoft resear...
30 篇 department of co...
25 篇 department of co...
23 篇 institute for co...
22 篇 department of co...
22 篇 school of comput...
20 篇 university of sc...
20 篇 swiss fed inst t...
19 篇 tsinghua univers...
19 篇 institute of com...
18 篇 swiss fed inst t...
17 篇 the robotics ins...
17 篇 carnegie mellon ...
17 篇 computer vision ...
17 篇 department of co...
16 篇 institute of inf...
16 篇 school of comput...
15 篇 school of comput...
15 篇 carnegie mellon ...
14 篇 national laborat...

作者

57 篇 timofte radu
25 篇 huang thomas s.
24 篇 van gool luc
23 篇 s.k. nayar
22 篇 nayar shree k.
22 篇 t. kanade
21 篇 jain anil k.
20 篇 luc van gool
19 篇 t.s. huang
18 篇 xiaoou tang
18 篇 murino vittorio
18 篇 horst bischof
17 篇 a.k. jain
17 篇 t. darrell
16 篇 g. healey
16 篇 bowyer kevin w.
16 篇 bischof horst
15 篇 m.j. black
15 篇 li stan z.
15 篇 m. shah

语言

8,932 篇 英文
21 篇 其他
8 篇 中文
1 篇 土耳其文

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

共 8962 条记录，以下是1271-1280 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：

Residual-based Language Models are Free Boosters for Biomedical Imaging Tasks

Residual-based Language Models are Free Boosters for Biomedi...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Zhixin Lai Jing Wu Suiyao Chen Yucheng Zhou Naira Hovakimyan Cornel University University of Illinois at Urbana-Champaign University of South Florida University of Macau

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

In this study, we uncover the unexpected efficacy of residual-based large language models (LLMs) as part of encoders for biomedical imaging tasks, a domain traditionally devoid of language or textual data. The approach diverges from established methodologies by utilizing a frozen transformer block, extracted from pre-trained LLMs, as an innovative encoder layer for the direct processing of visual tokens. This strategy represents a significant departure from the standard multi-modal vision-language frameworks, which typically hinge on language-driven prompts and inputs. We found that these LLMs could boost performance across a spectrum of biomedical imaging applications, including both 2D and 3D visual classification tasks, serving as plug-and-play boosters. More interestingly, as a byproduct, we found that the proposed framework achieved superior performance, setting new state-of-the-art results on extensive, standardized datasets in MedMNIST-2D and 3D. Through this work, we aim to open new avenues for employing LLMs in biomedical imaging and enriching the understanding of their potential in this specialized domain. The code is available at https://***/ZhixinLai/LLMBoostMedical

关键词： Visualization Three-dimensional displays Large language models conferences Fasteners Transformers pattern recognition

来源：评论

学校读者我要写书评

暂无评论

One Embedding to Predict Them All: Visible and Thermal Universal Face Representations for Soft Biometric Estimation via vision Transformers

One Embedding to Predict Them All: Visible and Thermal Unive...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Nelida Mirabet-Herranz Chiara Galdi Jean-Luc Dugelay Campus SophiaTech EURECOM France

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Human faces encode a vast amount of information including not only uniquely distinctive features of the individual but also demographic information such as a person’s age, gender, and weight. Such information is referred to as soft-biometrics, which are physical, behavioral or adhered human characteristics, classifiable in pre–defined human compliant categories. As we often say ’one look is worth a thousand words’. vision Transformers have emerged as a powerful deep learning architecture able to achieve accurate classifications for different computer vision tasks, but these models have not been yet applied to soft-biometrics. In this work, we propose the Bidirectional Encoder Face representation from image Transformers (BEFiT), a model that leverages the multi-attention mechanisms to capture local and global features and produce a multi-purpose face embedding. This unique embedding enables the estimation of different demographics without having to re-train the model for each soft-biometric trait, ensuring high efficiency without compromising accuracy. Our approach explores the use of visible and thermal images to achieve powerful face embedding in different light spectra. We demonstrate that the BEFiT embeddings can capture essential information for gender, age, and weight estimation, surpassing the performance of dedicated deep learning structures for the estimation of a single soft biometric trait. The code of BEFiT implementation is publicly available 1

关键词： Biometrics Training computer vision Accuracy Computational modeling Estimation Transformers

来源：评论

学校读者我要写书评

暂无评论

Domain Adaptation Using Pseudo Labels for COVID-19 Detection

Domain Adaptation Using Pseudo Labels for COVID-19 Detection

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Runtian Yuan Qingqiu Li Junlin Hou Jilan Xu Yuejie Zhang Rui Feng Hao Chen School of Computer Science Fudan University China School of Academy for Engineering and Technology Fudan University China Department of Computer Science and Engineering The Hong Kong University of Science and Technology China

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Deep learning has offered advanced analytical capabilities to enhance the accuracy and efficiency of detecting COVID-19 through complex pattern recognition in medical imaging data. However, the variability across datasets from different domains poses a significant challenge to the generalization abilities of deep learning models. In this paper, we propose a novel two-stage framework for domain adaptation of COVID-19 detection. Initially, We train a model on annotated data from both domains, integrating contrastive representation learning and a modified version of CORAL loss to minimize domain discrepancies. In the subsequent stage, we employ a pseudo-labeling strategy to effectively utilize non-annotated data from the target domain, further enhancing the model’s adaptability and performance. The effectiveness of our approach is demonstrated through extensive experiments, showing significant improvements in COVID-19 detection performance compared to the baseline model. On the COVID-19 domain adaptation leaderboard in the 4th COV19D Competition, our approach ranked 1st with a Macro F1 Score of 77.55%.

关键词： COVID-19 Representation learning Deep learning Training Adaptation models computer vision conferences

来源：评论

学校读者我要写书评

暂无评论

Light Field Synthesis from a Monocular Image using Variable LDI

Light Field Synthesis from a Monocular Image using Variable ...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Junhyeong Bak In Kyu Park Department of Electrical and Computer Engineering Inha University Incheon Korea

Recent advancements in learning-based novel view synthesis enable users to synthesize light field from a monocular image without special equipment. Moreover, the state-of-the-art techniques including multiplane image (MPI) show outstanding performance in synthesizing accurate light field from a monocular image. In this study, we propose a new variable layered depth image (VLDI) representation to generate precise light field synthesis results using only a few layers. Our method exploits LDI representation built on a new two-stream halfway fusion network and transformation process. This framework has an efficient structure that directly generates the region that does not require network prediction from inputs. As a result, the proposed method allows us to acquire high-quality light field easily and quickly. Experimental results show that the proposed method outperforms the previous works quantitatively and qualitatively for diverse examples.

关键词：

来源：评论

学校读者我要写书评

暂无评论

3DSAINT Representation for 3D Point Clouds

3DSAINT Representation for 3D Point Clouds

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Chandra Kambhamettu Video/Image Modeling and Synthesis (VIMS) Lab. Computer and Information Sciences University of Delaware Newark Delaware

This paper introduces a Sphere-based representation to model a 3D scene and show its performance on various tasks, including Structure from Motion (SfM) and 3D scene classification. A significant target application of this work is Mixed Reality, where 3D data can be efficiently represented, and synthetic and real data can be mixed for an immersive experience. Over the past few decades, 3D big data has garnered increased attention in computer vision. Acquiring, representing, reconstructing, querying, classifying, and visualizing 3D models for Mixed Reality has become crucial for many applications, such as medicine, architecture, entertainment, and bioinformatics. With the ever-increasing amount of data that the 3D scanners produce, storing, processing, and transmitting the data becomes challenging. Techniques that exploit the shape information need to be developed to model, classify and visualize the data. Our work offers a novel multi-scale surface representation based on spheres, with the ultimate goal of helping scientists to see and work with 3D data in Mixed Reality more effectively and efficiently.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Can the accuracy bias by facial hairstyle be reduced through balancing the training data?

Can the accuracy bias by facial hairstyle be reduced through...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Kagan Ozturk Haiyu Wu Kevin W. Bowyer University of Notre Dame

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Appearance of a face can be greatly altered by growing a beard and mustache. The facial hairstyles in a pair of images can cause marked changes to the impostor distribution and the genuine distribution. Also, different distributions of facial hairstyle across demographics could cause a false impression of relative accuracy across demographics. We first show that, even though larger training sets boost the recognition accuracy on all facial hairstyles, accuracy variations caused by facial hairstyles persist regardless of the size of the training set. Then, we analyze the impact of having different fractions of the training data represent facial hairstyles. We created balanced training sets using a set of identities available in Webface42M that both have clean-shaven and facial hair images. We find that, even when a face recognition model is trained with a balanced clean-shaven / facial hair training set, accuracy variation on the test data does not diminish. Next, data augmentation is employed to further investigate the effect of facial hair distribution in training data by manipulating facial hair pixels with the help of facial landmark points and a facial hair segmentation model. Our results show facial hair causes an accuracy gap between clean-shaven and facial hair images, and this impact can be significantly different between African-Americans and Caucasians.

关键词： Hair Training Image segmentation computer vision Accuracy Face recognition conferences

来源：评论

学校读者我要写书评

暂无评论

VMCML: Video and Music Matching via Cross-Modality Lifting

VMCML: Video and Music Matching via Cross-Modality Lifting

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Yi-Shan Lee Wei-Cheng Tseng Fu-En Wang Min Sun National Tsing Hua University University of Toronto Vector Institute

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

We propose a content-based system for matching video and background music. The system aims to address the challenges in music recommendation for new users or new music give short-form videos. To this end, we propose a cross-modal framework VMCML (Video and Music Matching via Cross-Modality Lifting) that finds a shared embedding space between video and music representations. To ensure the embedding space can be effectively shared by both representations, we leverage CosFace loss based on margin-based cosine similarity loss. Furthermore, to confirm the music is not the original sound of the video and that more than one video is matched to the same music, we follow the rule and collect videos and music from a well-known multi-media platform. That is because there are limitations of previous datasets. We establish a large-scale dataset called MSV, which provide 390 individual music and the corresponding matched 150,000 videos. We conduct extensive experiments on Youtube-8M and our MSV datasets. Our quantitative and qualitative results demonstrate the effectiveness of our proposed framework and achieve state-of-the-art video and music matching performance.

关键词： computer vision conferences Music Recommender systems pattern matching

来源：评论

学校读者我要写书评

暂无评论

Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupervised Domain Adaptation

Achieving Reliable and Fair Skin Lesion Diagnosis via Unsupe...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Janet Wang Yunbei Zhang Zhengming Ding Jihun Hamm Tulane University

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

The development of reliable and fair diagnostic systems is often constrained by the scarcity of labeled data. To address this challenge, our work explores the feasibility of unsupervised domain adaptation (UDA) to integrate large external datasets for developing reliable classifiers. The adoption of UDA with multiple sources can simultaneously enrich the training set and bridge the domain gap between different skin lesion datasets, which vary due to distinct acquisition protocols. Particularly, UDA shows practical promise for improving diagnostic reliability when training with a custom skin lesion dataset, where only limited labeled data are available from the target domain. In this study, we investigate three UDA training schemes based on source data utilization: single-source, combined-source, and multi-source UDA. Our findings demonstrate the effectiveness of applying UDA on multiple sources for binary and multi-class classification. A strong correlation between test error and label shift in multi-class tasks has been observed in the experiment. Crucially, our study shows that UDA can effectively mitigate bias against minority groups and enhance fairness in diagnostic systems, while maintaining superior classification performance. This is achieved even without directly implementing fairness-focused techniques. This success is potentially attributed to the increased and well-adapted demographic information obtained from multiple sources.

关键词： Training computer vision Protocols Correlation conferences Skin pattern recognition

来源：评论

学校读者我要写书评

暂无评论

ViTKD: Feature-based Knowledge Distillation for vision Transformers

ViTKD: Feature-based Knowledge Distillation for Vision Trans...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Zhendong Yang Zhe Li Ailing Zeng Zexian Li Chun Yuan Yu Li Tsinghua Shenzhen International Graduate School International Digital Economy Academy (IDEA) Institute of Automation Chinese Academy of Sciences Beihang University

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Knowledge Distillation (KD) has been extensively studied as a means to enhance the performance of smaller models in Convolutional Neural Networks (CNNs). Recently, the vision Transformer (ViT) has demonstrated remarkable success in various computer vision tasks, leading to an increased demand for KD in ViT. However, while logit-based KD has been applied to ViT, other feature-based KD methods for CNNs cannot be directly implemented due to the significant structure gap. In this paper, we conduct an analysis of the properties of different feature layers in ViT to identify a method for feature-based ViT distillation. Our findings reveal that both shallow and deep layers in ViT are equally important for distillation and require distinct distillation strategies. Based on these guidelines, we propose our feature-based method ViTKD, which mimics the shallow layers and generates the deep layer in the teacher. ViTKD leads to consistent and significant improvements in the students. On ImageNet-1K, we achieve performance boosts of 1.64% for DeiT-Tiny, 1.40% for DeiT-Small, and 1.70% for DeiT-Base. Downstream tasks also demonstrate the superiority of ViTKD. Additionally, ViTKD and logit-based KD are complementary and can be applied together directly, further enhancing the student’s performance. Specifically, DeiT-T, S, and B achieve accuracies of 77.78%, 83.59%, and 85.41%, respectively, using this combined approach. Code is available at https://***/yzd-v/cls_KD.

关键词： Knowledge engineering computer vision conferences Computational modeling MIMICs Transformers pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Sparse multi-view hand-object reconstruction for unseen environments

Sparse multi-view hand-object reconstruction for unseen envi...

引用

ieee computer society conference on computer vision and pattern recognition workshops (CVPRW)

作者： Yik Lung Pang Changjae Oh Andrea Cavallaro Centre for Intelligent Sensing Queen Mary University of London Idiap Research Institute École Polytechnique Fédérale de Lausanne

ISBN: (数字)9798350365474

ISBN: (纸本)9798350365481

Recent works in hand-object reconstruction mainly focus on the single-view and dense multi-view settings. On the one hand, single-view methods can leverage learned shape priors to generalise to unseen objects but are prone to inaccuracies due to occlusions. On the other hand, dense multi-view methods are very accurate but cannot easily adapt to unseen objects without further data collection. In contrast, sparse multi-view methods can take advantage of the additional views to tackle occlusion, while keeping the computational cost low compared to dense multi-view methods. In this paper, we consider the problem of hand-object reconstruction with unseen objects in the sparse multi-view setting. Given multiple RGB images of the hand and object captured at the same time, our model SVHO combines the predictions from each view into a unified reconstruction without optimisation across views. We train our model on a synthetic hand-object dataset and evaluate directly on a real world recorded hand-object dataset with unseen objects. We show that while reconstruction of unseen hands and objects from RGB is challenging, additional views can help improve the reconstruction quality.

关键词： computer vision Shape Computational modeling conferences Predictive models Data collection 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 << < 124 125 126 127 128 129 130 131 132 133 > >>

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：