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

11,267 篇 会议
14 篇 期刊文献

馆藏范围

11,281 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

7,859 篇 工学
- 7,418 篇 计算机科学与技术...
- 799 篇 机械工程
- 390 篇 电气工程
- 377 篇 软件工程
- 224 篇 控制科学与工程
- 68 篇 光学工程
- 32 篇 信息与通信工程
- 26 篇 生物工程
- 10 篇 生物医学工程（可授...
- 8 篇 化学工程与技术
- 7 篇 电子科学与技术（可...
- 6 篇 交通运输工程
- 5 篇 安全科学与工程
- 3 篇 仪器科学与技术
- 2 篇 力学（可授工学、理...
- 2 篇 材料科学与工程（可...
- 2 篇 动力工程及工程热...
- 2 篇 航空宇航科学与技...
3,103 篇 医学
- 3,102 篇 临床医学
- 4 篇 基础医学(可授医学...
297 篇 理学
- 199 篇 系统科学
- 69 篇 物理学
- 27 篇 生物学
- 24 篇 数学
- 9 篇 统计学（可授理学、...
- 7 篇 化学
23 篇 管理学
- 14 篇 图书情报与档案管...
- 9 篇 管理科学与工程(可...
- 4 篇 工商管理
6 篇 法学
- 6 篇 社会学
2 篇 农学
1 篇 教育学
1 篇 艺术学

主题

5,461 篇 computer vision
2,564 篇 training
2,118 篇 pattern recognit...
1,632 篇 computational mo...
1,454 篇 visualization
1,325 篇 three-dimensiona...
1,070 篇 semantics
972 篇 codes
968 篇 benchmark testin...
930 篇 computer archite...
885 篇 deep learning
831 篇 task analysis
729 篇 feature extracti...
541 篇 conferences
530 篇 neural networks
526 篇 face recognition
503 篇 transformers
480 篇 object detection
478 篇 image segmentati...
469 篇 cameras

机构

169 篇 univ sci & techn...
146 篇 tsinghua univ pe...
142 篇 univ chinese aca...
142 篇 carnegie mellon ...
132 篇 chinese univ hon...
122 篇 peng cheng lab p...
102 篇 zhejiang univ pe...
96 篇 sensetime res pe...
95 篇 swiss fed inst t...
90 篇 shanghai ai lab ...
86 篇 tsinghua univers...
86 篇 stanford univ st...
84 篇 shanghai jiao to...
80 篇 zhejiang univers...
79 篇 alibaba grp peop...
79 篇 univ hong kong p...
76 篇 peng cheng labor...
76 篇 tech univ munich...
74 篇 australian natl ...
73 篇 peking univ peop...

作者

67 篇 timofte radu
60 篇 van gool luc
50 篇 zhang lei
43 篇 yang yi
36 篇 loy chen change
36 篇 tao dacheng
31 篇 liu yang
30 篇 zhou jie
30 篇 chen chen
30 篇 tian qi
29 篇 sun jian
28 篇 zha zheng-jun
27 篇 qi tian
27 篇 boxin shi
26 篇 li xin
26 篇 vasconcelos nuno
26 篇 pollefeys marc
24 篇 liu xiaoming
24 篇 zheng wei-shi
24 篇 luo ping

语言

11,273 篇 英文
7 篇 其他
1 篇 中文

检索条件"任意字段=2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2020"

共 11281 条记录，以下是531-540 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：

Plateau-reduced Differentiable Path Tracing

Plateau-reduced Differentiable Path Tracing

引用

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

作者： Fischer, Michael Ritschel, Tobias UCL London England

ISBN: (纸本)9798350301298

Current differentiable renderers provide light transport gradients with respect to arbitrary scene parameters. However, the mere existence of these gradients does not guarantee useful update steps in an optimization. Instead, inverse rendering might not converge due to inherent plateaus, i.e., regions of zero gradient, in the objective function. We propose to alleviate this by convolving the high-dimensional rendering function, that maps scene parameters to images, with an additional kernel that blurs the parameter space. We describe two Monte Carlo estimators to compute plateau-reduced gradients efficiently, i.e., with low variance, and show that these translate into net-gains in optimization error and runtime performance. Our approach is a straightforward extension to both black-box and differentiable renderers and enables optimization of problems with intricate light transport, such as caustics or global illumination, that existing differentiable renderers do not converge on. Our code is at ***/mfischerucl/prdpt.

关键词： vision + graphics

来源：评论

学校读者我要写书评

暂无评论

Adaptive Channel Sparsity for Federated Learning under System Heterogeneity

Adaptive Channel Sparsity for Federated Learning under Syste...

引用

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

作者： Liao, Dongping Gao, Xitong Zhao, Yiren Xu, Chengzhong Univ Macau State Key Lab IoTSC CIS Dept Taipa Macau Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Imperial Coll London London England

ISBN: (纸本)9798350301298

Owing to the non-i.i.d. nature of client data, channel neurons in federated-learned models may specialize to distinct features for different clients. Yet, existing channel-sparse federated learning (FL) algorithms prescribe fixed sparsity strategies for client models, and may thus prevent clients from training channel neurons collaboratively. To minimize the impact of sparsity on FL convergence, we propose Flado to improve the alignment of client model update trajectories by tailoring the sparsities of individual neurons in each client. Empirical results show that while other sparse methods are surprisingly impactful to convergence, Flado can not only attain the highest task accuracies with unlimited budget across a range of datasets, but also significantly reduce the amount of floating-point operations (FLOPs) required for training more than by 10 x under the same communications budget, and push the Pareto frontier of communication/computation trade-off notably further than competing FL algorithms.

关键词： Efficient and scalable vision

来源：评论

学校读者我要写书评

暂无评论

Recurrent Homography Estimation Using Homography-Guided Image Warping and Focus Transformer

Recurrent Homography Estimation Using Homography-Guided Imag...

引用

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

作者： Cao, Si-Yuan Zhang, Runmin Luo, Lun Yu, Beinan Sheng, Zehua Li, Junwei Shen, Hui-Liang Zhejiang Univ Ningbo Innovat Ctr Hangzhou Peoples R China Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou Peoples R China

ISBN: (纸本)9798350301298

We propose the Recurrent homography estimation framework using Homography-guided image Warping and Focus transformer (FocusFormer), named RHWF. Both being appropriately absorbed into the recurrent framework, the homography-guided image warping progressively enhances the feature consistency and the attention-focusing mechanism in FocusFormer aggregates the intra-inter correspondence in a global -> nonlocal -> local manner. Thanks to the above strategies, RHWF ranks top in accuracy on a variety of datasets, including the challenging cross-resolution and cross-modal ones. Meanwhile, benefiting from the recurrent framework, RHWF achieves parameter efficiency despite the transformer architecture. Compared to previous state-of-the-art approaches LocalTrans and IHN, RHWF reduces the mean average corner error (MACE) by about 70% and 38.1% on the MSCOCO dataset, while saving the parameter costs by 86.5% and 24.6%. Similar to the previous works, RHWF can also be arranged in 1-scale for efficiency and 2-scale for accuracy, with the 1-scale RHWF already outperforming most of the previous methods. Source code is available at https://***/imdumpl78/RHWF.

关键词： Low-level vision

来源：评论

学校读者我要写书评

暂无评论

GRAFIQS: Face Image Quality Assessment Using Gradient Magnitudes

GRAFIQS: Face Image Quality Assessment Using Gradient Magnit...

引用

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

作者： Kolf, Jan Niklas Damer, Naser Boutros, Fadi Fraunhofer Inst Comp Graph Res IGD Darmstadt Germany Tech Univ Darmstadt Darmstadt Germany

ISBN: (纸本)9798350365474

Face Image Quality Assessment (FIQA) estimates the utility of face images for automated face recognition (FR) systems. We propose in this work a novel approach to assess the quality of face images based on inspecting the required changes in the pre-trained FR model weights to minimize differences between testing samples and the distribution of the FR training dataset. To achieve that, we propose quantifying the discrepancy in Batch Normalization statistics (BNS), including mean and variance, between those recorded during FR training and those obtained by processing testing samples through the pretrained FR model. We then generate gradient magnitudes of pretrained FR weights by backpropagating the BNS through the pretrained model. The cumulative absolute sum of these gradient magnitudes serves as the FIQ for our approach. Through comprehensive experimentation, we demonstrate the effectiveness of our training-free and quality labeling-free approach, achieving competitive performance to recent state-of-the-art FIQA approaches without relying on quality labeling, the need to train regression networks, specialized architectures, or designing and optimizing specific loss functions.

关键词： Biometrics computer vision Face Image Quality Assessment Face recognition

来源：评论

学校读者我要写书评

暂无评论

Texts as Images in Prompt Tuning for Multi-Label Image recognition

Texts as Images in Prompt Tuning for Multi-Label Image Recog...

引用

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

作者： Guo, Zixian Dong, Bowen Ji, Zhilong Bai, Jinfeng Guo, Yiwen Zuo, Wangmeng Harbin Inst Technol Harbin Peoples R China Tomorrow Adv Life Beijing Peoples R China Pazhou Lab Guangzhou Peoples R China

ISBN: (纸本)9798350301298

Prompt tuning has been employed as an efficient way to adapt large vision-language pre-trained models (e.g. CLIP) to various downstream tasks in data-limited or label-limited settings. Nonetheless, visual data (e.g., images) is by default prerequisite for learning prompts in existing methods. In this work, we advocate that the effectiveness of image-text contrastive learning in aligning the two modalities (for training CLIP) further makes it feasible to treat texts as images for prompt tuning and introduce TaI prompting. In contrast to the visual data, text descriptions are easy to collect, and their class labels can be directly derived. Particularly, we apply TaI prompting to multi-label image recognition, where sentences in the wild serve as alternatives to images for prompt tuning. Moreover, with TaI, double-grained prompt tuning (TaI-DPT) is further presented to extract both coarse-grained and fine-grained embeddings for enhancing the multi-label recognition performance. Experimental results show that our proposed TaI-DPT outperforms zero-shot CLIP by a large margin on multiple benchmarks, e.g., MS-COCO, VOC2007, and NUS-WIDE, while it can be combined with existing methods of prompting from images to improve recognition performance further. The code is released at https://***/guozix/TaI-DPT.

关键词： continual low-shot meta or long-tail learning Transfer

来源：评论

学校读者我要写书评

暂无评论

Multiclass Confidence and Localization Calibration for Object Detection

Multiclass Confidence and Localization Calibration for Objec...

引用

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

作者： Pathiraja, Bimsara Gunawardhana, Malitha Khan, Muhammad Haris Mohamed Bin Zayed Univ Artificial Intelligence Abu Dhabi U Arab Emirates

ISBN: (纸本)9798350301298

Albeit achieving high predictive accuracy across many challenging computer vision problems, recent studies suggest that deep neural networks (DNNs) tend to make overconfident predictions, rendering them poorly calibrated. Most of the existing attempts for improving DNN calibration are limited to classification tasks and restricted to calibrating in-domain predictions. Surprisingly, very little to no attempts have been made in studying the calibration of object detection methods, which occupy a pivotal space in vision-based security-sensitive, and safety-critical applications. In this paper, we propose a new train-time technique for calibrating modern object detection methods. It is capable of jointly calibrating multiclass confidence and box localization by leveraging their predictive uncertainties. We perform extensive experiments on several in-domain and out-of-domain detection benchmarks. Results demonstrate that our proposed train-time calibration method consistently outperforms several baselines in reducing calibration error for both in-domain and out-of-domain predictions. Our code and models are available at https: //***/bimsarapathiraja/MCCL

关键词： vision applications and systems

来源：评论

学校读者我要写书评

暂无评论

Coarse or Fine? Recognising Action End States without Labels

Coarse or Fine? Recognising Action End States without Labels

引用

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

作者： Moltisanti, Davide Bilen, Hakan Sevilla-Lara, Laura Keller, Frank Univ Bath Bath Avon England Univ Edinburgh Edinburgh Midlothian Scotland

ISBN: (纸本)9798350365474

We focus on the problem of recognising the end state of an action in an image, which is critical for understanding what action is performed and in which manner. We study this focusing on the task of predicting the coarseness of a cut, i.e., deciding whether an object was cut "coarsely" or "finely". No dataset with these annotated end states is available, so we propose an augmentation method to synthesise training data. We apply this method to cutting actions extracted from an existing action recognition dataset. Our method is object agnostic, i.e., it presupposes the location of the object but not its identity. Starting from less than a hundred images of a whole object, we can generate several thousands images simulating visually diverse cuts of different coarseness. We use our synthetic data to train a model based on UNet and test it on real images showing coarsely/finely cut objects. Results demonstrate that the model successfully recognises the end state of the cutting action despite the domain gap between training and testing, and that the model generalises well to unseen objects.

关键词： adverb recognition fine-grained recognition object end-state recognition

来源：评论

学校读者我要写书评

暂无评论

Visual Programming: Compositional visual reasoning without training

Visual Programming: Compositional visual reasoning without t...

引用

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

作者： Gupta, Tanmay Kembhavi, Aniruddha PRIOR Allen Inst AI Seattle WA 98103 USA

ISBN: (纸本)9798350301298

We present VISPROG, a neuro-symbolic approach to solving complex and compositional visual tasks given natural language instructions. VISPROG avoids the need for any task-specific training. Instead, it uses the in-context learning ability of large language models to generate python-like modular programs, which are then executed to get both the solution and a comprehensive and interpretable rationale. Each line of the generated program may invoke one of several off-the-shelf computer vision models, image processing subroutines, or python functions to produce intermediate outputs that may be consumed by subsequent parts of the program. We demonstrate the flexibility of VISPROG on 4 diverse tasks - compositional visual question answering, zero-shot reasoning on image pairs, factual knowledge object tagging, and language-guided image editing. We believe neuro-symbolic approaches like VISPROG are an exciting avenue to easily and effectively expand the scope of AI systems to serve the long tail of complex tasks that people may wish to perform.

关键词： and reasoning language vision

来源：评论

学校读者我要写书评

暂无评论

FairCLIP: Harnessing Fairness in vision-Language Learning

FairCLIP: Harnessing Fairness in Vision-Language Learning

引用

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

作者： Luol, Yan Shil, Min Khan, Muhammad Osama Afzal, Muhammad Muneeb Huang, Hao Yuan, Shuaihang Tian, Yu Song, Luo Kouhana, Ava Elze, Tobias Fang, Yi Wang, Mengyu Harvard Univ Harvard Ophthalmol AI Lab Cambridge MA 02138 USA NYU Tandon Sch Engn New York NY USA New York Univ Abu Dhabi Multimedia & Visual Comp Lab Abu Dhabi U Arab Emirates

ISBN: (纸本)9798350353006

Fairness is a critical concern in deep learning, especially in healthcare, where these models influence diagnoses and treatment decisions. Although fairness has been investigated in the vision-only domain, the fairness of medical vision-language (VL) models remains unexplored due to the scarcity of medical VL datasets for studying fairness. To bridge this research gap, we introduce the first fair vision-language medical dataset (Harvard-FairVLMed) that provides detailed demographic attributes, ground-truth labels, and clinical notes to facilitate an in-depth examination of fairness within VL foundation models. Using Harvard-FairVLMed, we conduct a comprehensive fairness analysis of two widely-used VL models (CLIP and BLIP2), pre-trained on both natural and medical domains, across four different protected attributes. Our results highlight significant biases in all VL models, with Asian, Male, Non-Hispanic, and Spanish being the preferred subgroups across the protected attributes of race, gender, ethnicity, and language, respectively. In order to alleviate these biases, we propose FairCLIP, an optimal-transport-based approach that achieves a favorable trade-off between performance and fairness by reducing the Sinkhorn distance between the overall sample distribution and the distributions corresponding to each demographic group. As the first VL dataset of its kind, Harvard-FairVLMed holds the potential to catalyze advancements in the development of machine learning models that are both ethically aware and clinically effective. Our dataset and code are available at https://***/datasets/

关键词： AI for Medicine Equitable Deep Learning Fairness Learning Large Language Models Medical AI Ophthalmology Optimal Transport vision-Language Learning

来源：评论

学校读者我要写书评

暂无评论

A Dual-Mode Approach for vision-Based Navigation in a Lunar Landing Scenario

A Dual-Mode Approach for Vision-Based Navigation in a Lunar ...

引用

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

作者： Ostrogovich, Luca Del Prete, Roberto Tomasicchio, Giuseppe Longepe, Nicolas Renga, Alfredo Univ Naples Federico II Dept Ind Engn Naples Italy Telespazio SRL Rome Italy ESA ESRIN Lab Frascati Italy

ISBN: (纸本)9798350365474

In this research, a novel approach for autonomous spacecraft navigation, particularly in lunar contexts, is presented, focusing on vision-based techniques. The system incorporates lunar crater recognition in conjunction with feature tracking to enhance the accuracy of spacecraft navigation. This system underwent comprehensive evaluation through a purpose-built software simulation, replicating lunar conditions for thorough evaluation and refinement. The methodology integrates established navigational methods with advanced artificial intelligence algorithms, resulting in significant navigational accuracy. The system demonstrates precise capabilities in determining the spacecraft position, with an average accuracy of approximately 270 m for the absolute navigation mode, while the relative mode exhibited an average error of 27.4 m and 0.8 m in determining the horizontal and vertical lander displacements relative to terrain. Initial tests on embedded systems-akin to those on-board spacecraft-were conducted. These tests are pivotal in demonstrating the system's operational viability within the constraints of limited bandwidth and rapid processing requirements characteristic of space missions. The promising results from these tests suggest potential applicability in real-world space missions, enhancing autonomous navigation capabilities in lunar and potentially other extraterrestrial environments.

关键词： Lunar Navigation Onboard AI Visual Based Navigation

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 << < 50 51 52 53 54 55 56 57 58 59 > >>

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：