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

11,885 篇 会议
5 篇 期刊文献

馆藏范围

11,890 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

8,059 篇 工学
- 7,617 篇 计算机科学与技术...
- 796 篇 机械工程
- 688 篇 电气工程
- 360 篇 软件工程
- 228 篇 控制科学与工程
- 40 篇 光学工程
- 19 篇 生物工程
- 17 篇 信息与通信工程
- 12 篇 生物医学工程（可授...
- 6 篇 电子科学与技术（可...
- 6 篇 建筑学
- 6 篇 交通运输工程
- 5 篇 仪器科学与技术
- 5 篇 化学工程与技术
- 5 篇 安全科学与工程
- 4 篇 土木工程
3,347 篇 医学
- 3,346 篇 临床医学
- 4 篇 基础医学(可授医学...
- 4 篇 公共卫生与预防医...
253 篇 理学
- 198 篇 系统科学
- 32 篇 物理学
- 21 篇 生物学
- 18 篇 数学
- 9 篇 统计学（可授理学、...
- 7 篇 化学
17 篇 管理学
- 12 篇 管理科学与工程(可...
- 7 篇 图书情报与档案管...
- 5 篇 工商管理
3 篇 法学
- 3 篇 社会学
3 篇 教育学
- 3 篇 教育学
2 篇 农学
1 篇 经济学
1 篇 军事学

主题

5,633 篇 computer vision
2,668 篇 training
2,203 篇 pattern recognit...
1,747 篇 computational mo...
1,502 篇 visualization
1,360 篇 three-dimensiona...
1,074 篇 semantics
999 篇 benchmark testin...
986 篇 codes
959 篇 computer archite...
891 篇 deep learning
777 篇 conferences
754 篇 task analysis
700 篇 feature extracti...
561 篇 transformers
533 篇 face recognition
527 篇 neural networks
495 篇 object detection
490 篇 image segmentati...
468 篇 cameras

机构

174 篇 univ sci & techn...
145 篇 carnegie mellon ...
144 篇 univ chinese aca...
144 篇 tsinghua univ pe...
134 篇 chinese univ hon...
110 篇 zhejiang univ pe...
109 篇 peng cheng lab p...
99 篇 swiss fed inst t...
91 篇 tsinghua univers...
90 篇 shanghai ai lab ...
87 篇 sensetime res pe...
86 篇 shanghai jiao to...
83 篇 zhejiang univers...
82 篇 tech univ munich...
79 篇 university of sc...
79 篇 stanford univ st...
78 篇 univ hong kong p...
77 篇 australian natl ...
76 篇 alibaba grp peop...
75 篇 peng cheng labor...

作者

75 篇 timofte radu
64 篇 van gool luc
50 篇 zhang lei
43 篇 yang yi
37 篇 loy chen change
36 篇 tao dacheng
32 篇 zhou jie
31 篇 chen chen
30 篇 liu yang
30 篇 tian qi
29 篇 sun jian
29 篇 zha zheng-jun
28 篇 li xin
27 篇 qi tian
26 篇 vasconcelos nuno
25 篇 liu xiaoming
25 篇 darrell trevor
24 篇 zheng wei-shi
24 篇 luo ping
24 篇 ying shan

语言

11,863 篇 英文
26 篇 其他
1 篇 中文

检索条件"任意字段=2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024"

共 11890 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：

Behavioral Analysis of vision-and-Language Navigation Agents

Behavioral Analysis of Vision-and-Language Navigation Agents

引用

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

作者： Yang, Zijiao Majumdar, Arjun Lee, Stefan Oregon State Univ Corvallis OR 97331 USA Georgia Inst Technol Atlanta GA USA

ISBN: (纸本)9798350301298

To be successful, vision-and-Language Navigation (VLN) agents must be able to ground instructions to actions based on their surroundings. In this work, we develop a methodology to study agent behavior on a skill-specific basis - examining how well existing agents ground instructions about stopping, turning, and moving towards specified objects or rooms. Our approach is based on generating skill-specific interventions and measuring changes in agent predictions. We present a detailed case study analyzing the behavior of a recent agent and then compare multiple agents in terms of skill-specific competency scores. This analysis suggests that biases from training have lasting effects on agent behavior and that existing models are able to ground simple referring expressions. Our comparisons between models show that skill-specific scores correlate with improvements in overall VLN task performance.

关键词： language reasoning vision

来源：评论

学校读者我要写书评

暂无评论

Convolutional Relational Machine for Group Activity recognition 32

Convolutional Relational Machine for Group Activity Recognit...

引用

32nd ieee/cvf conference on computer vision and pattern recognition (cvpr)

作者： Azar, Sina Mokhtarzadeh Atigh, Mina Ghadimi Nickabadi, Ahmad Alahi, Alexandre Amirkabir Univ Technol AUT SML Lab 424 Hafez Ave Tehran Iran Ecole Polytech Fed Lausanne EPFL VITA Lab CH-1015 Lausanne Switzerland

ISBN: (纸本)9781728132938

We present an end-to-end deep Convolutional Neural Network called Convolutional Relational Machine (CRM) for recognizing group activities that utilizes the information in spatial relationsbetween individualpersons in image or video. It learns to produce an intermediate spatial representation (activity map) based on individual and group activities. A multi-stage refinement component is responsible for decreasingthe incorrectpredictions in the activity map. Finally, an aggregationcomponent uses the refined information to recognize group activities. Experimental results demonstrate the constructive contribution of the information extracted and represented in the form of the activity map. CRM shows advantages over state-of-the-artmodels on Volleyball and Collective Activity datasets.

关键词： Action recognition Deep Learning

来源：评论

学校读者我要写书评

暂无评论

Differentiable Patch Selection for Image recognition

Differentiable Patch Selection for Image Recognition

引用

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

作者： Cordonnier, Jean-Baptiste Mahendran, Aravindh Dosovitskiy, Alexey Weissenborn, Dirk Uszkoreit, Jakob Unterthiner, Thomas Ecole Polytech Fed Lausanne Lausanne Switzerland Google Res Brain Team Mountain View CA USA

ISBN: (纸本)9781665445092

Neural Networks require large amounts of memory and compute to process high resolution images, even when only a small part of the image is actually informative for the task at hand. We propose a method based on a differentiable Top-K operator to select the most relevant parts of the input to efficiently process high resolution images. Our method may be interfaced with any downstream neural network, is able to aggregate information from different patches in a flexible way, and allows the whole model to be trained end-to-end using backpropagation. We show results for traffic sign recognition, inter-patch relationship reasoning, and fine-grained recognition without using object/part bounding box annotations during training.

关键词： Training computer vision Image resolution Image recognition Computational modeling Neural networks Memory management

来源：评论

学校读者我要写书评

暂无评论

Analyzing Filters Toward Efficient ConvNet 31

Analyzing Filters Toward Efficient ConvNet

引用

31st ieee/cvf conference on computer vision and pattern recognition (cvpr)

作者： Kobayashi, Takumi Natl Inst Adv Ind Sci & Technol Tokyo Japan

ISBN: (纸本)9781538664209

Deep convolutional neural network (ConvNet) is a promising approach for high-performance image classification. The behavior of ConvNet is analyzed mainly based on the neuron activations, such as by visualizing them. In this paper, in contrast to the activations, we focus on filters which are main components of ConvNets. Through analyzing two types of filters at convolution and fully-connected (FC) layers, respectively, on various pre-trained ConvNets, we present the methods to efficiently reformulate the filters, contributing to improving both memory size and classification performance of the ConvNets. They render the filter bases formulated in a parameter-free form as well as the efficient representation for the FC layer. The experimental results on image classification show that the methods are favorably applied to improve various ConvNets, including ResNet, trained on ImageNet with exhibiting high transferability on the other datasets.

关键词： Convolution Feature extraction Neurons Image reconstruction Visualization Shape computer vision

来源：评论

学校读者我要写书评

暂无评论

Strategies to Improve Real-World Applicability of Laparoscopic Anatomy Segmentation Models

Strategies to Improve Real-World Applicability of Laparoscop...

引用

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

作者： Kolbinger, Fiona R. He, Jiangpeng Ma, Jinge Zhu, Fengqing Purdue Univ W Lafayette IN 47907 USA

ISBN: (纸本)9798350365474

Accurate identification and localization of anatomical structures of varying size and appearance in laparoscopic imaging are necessary to leverage the potential of computer vision techniques for surgical decision support. Segmentation performance of such models is traditionally reported using metrics of overlap such as IoU. However, imbalanced and unrealistic representation of classes in the training data and suboptimal selection of reported metrics have the potential to skew nominal segmentation performance and thereby ultimately limit clinical translation. In this work, we systematically analyze the impact of class characteristics (i.e., organ size differences), training and test data composition (i.e., representation of positive and negative examples), and modeling parameters (i.e., foreground-to-background class weight) on eight segmentation metrics: accuracy, precision, recall, IoU, F1 score (Dice Similarity Coefficient), specificity, Hausdorff Distance, and Average Symmetric Surface Distance. Our findings support two adjustments to account for data biases in surgical data science: First, training on datasets that are similar to the clinical real-world scenarios in terms of class distribution, and second, class weight adjustments to optimize segmentation model performance with regard to metrics of particular relevance in the respective clinical setting.

关键词： Class Imbalance computer-Assisted Surgery Laparoscopic Surgery Semantic Segmentation Surgical Data Science

来源：评论

学校读者我要写书评

暂无评论

Quasi-Unsupervised Color Constancy 32

Quasi-Unsupervised Color Constancy

引用

32nd ieee/cvf conference on computer vision and pattern recognition (cvpr)

作者： Bianco, Simone Cusano, Claudio Univ Milano Bicocca Milan Italy Univ Pavia Pavia Italy

ISBN: (纸本)9781728132938

We present here a method for computational color constancy in which a deep convolutional neural network is trained to detect achromatic pixels in color images after they have been converted to grayscale. The method does not require any information about the illuminant in the scene and relies on the weak assumption, fulfilled by almost all images available on the Web, that training images have been approximately balanced. Because of this requirement we define our method as quasi-unsupervised. After training, unbalanced images can be processed thanks to the preliminary conversion to grayscale of the input to the neural network. The results of an extensive experimentation demonstrate that the proposed method is able to outperform the other unsupervised methods in the state of the art being, at the same time, flexible enough to be supervisedly fine-tuned to reach performance comparable with those of the best supervised methods.

关键词： Computational Photography Deep Learning Low-level vision

来源：评论

学校读者我要写书评

暂无评论

ImplicitAtlas: Learning Deformable Shape Templates in Medical Imaging

ImplicitAtlas: Learning Deformable Shape Templates in Medica...

引用

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

作者： Yang, Jiancheng Wickramasinghe, Udaranga Ni, Bingbing Fua, Pascal Shanghai Jiao Tong Univ Shanghai Peoples R China Ecole Polytech Fed Lausanne Lausanne Switzerland

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

Deep implicit shape models have become popular in the computer vision community at large but less so for biomedical applications. This is in part because large training databases do not exist and in part because biomedical annotations are often noisy. In this paper;we show that by introducing templates within the deep learning pipeline we can overcome these problems. The proposed framework, named ImplicitAtlas, represents a shape as a deformation field from a learned template field, where multiple templates could be integrated to improve the shape representation capacity at negligible computational cost. Extensive experiments on three medical shape datasets prove the superiority over current implicit representation methods.

关键词： Training computer vision Three-dimensional displays Shape Pipelines Sensors pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Convolutions for Spatial Interaction Modeling

Convolutions for Spatial Interaction Modeling

引用

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

作者： Su, Zhaoen Wang, Chao Bradley, David Vallespi-Gonzalez, Carlos Wellington, Carl Djuric, Nemanja

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

In many different fields interactions between objects play a critical role in determining their behavior. Graph neural networks (GNNs) have emerged as a powerful tool for modeling interactions, although often at the cost of adding considerable complexity and latency. In this paper, we consider the problem of spatial interaction modeling in the context of predicting the motion of actors around autonomous vehicles, and investigate alternatives to GNNs. We revisit 2D convolutions and show that they can demonstrate comparable performance to graph networks in modeling spatial interactions with lower latency, thus providing an effective and efficient alternative in time-critical systems. Moreover, we propose a novel interaction loss to further improve the interaction modeling of the considered methods.

关键词： Tracking Navigation Computational modeling Predictive models Graph neural networks Complexity theory pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Breaking the cycle-Colleagues are all you need

Breaking the cycle-Colleagues are all you need

引用

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

作者： Nizan, Ori Tal, Ayellet Technion Israel Inst Technol Haifa Israel

ISBN: (纸本)9781728171685

This paper proposes a novel approach to performing image-to-image translation between unpaired domains. Rather than relying on a cycle constraint, our method takes advantage of collaboration between various GANs. This results in a multi-modal method, in which multiple optional and diverse images are produced for a given image. Our model addresses some of the shortcomings of classical GANs: (1) It is able to remove large objects, such as glasses. (2) Since it does not need to support the cycle constraint, no irrelevant traces of the input are left on the generated image. (3) It manages to translate between domains that require large shape modifications. Our results are shown to outperform those generated by state-of-the-art methods for several challenging applications.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

FIQA-FAS: Face Image Quality Assessment Based Face Anti-Spoofing

FIQA-FAS: Face Image Quality Assessment Based Face Anti-Spoo...

引用

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

作者： Liang, Ya-Chi Qiu, Min-Xuan Lai, Shang-Hong Natl Tsing Hua Univ Hsinchu Taiwan

ISBN: (纸本)9798350365474

Face anti-spoofing (FAS) is to protect facial recognition systems against presentation attacks. However, recent research on FAS often neglects real-world conditions, such as changing illumination, varying angles of face, and motion blur within a video. These conditions lead to inconsistent feature quality across face images, where low-quality features can cause the model to learn unreliable information during training. Moreover, frames with low feature quality within videos result in inaccurate decisions. To address this issue, we propose the Face Image Quality Assessment Based Face Anti-Spoofing System (FIQA-FAS), which integrates a face image quality assessment module with a face anti-spoofing module. FIQA-FAS assesses the feature quality extracted from each face image and uses the quality score to compute a weighted prediction for deciding if the face in a video is live or spoof. We demonstrate the effectiveness of FIQA-FAS through experiments on the SIW and SIW-M datasets. To further demonstrate our model's capabilities, we introduce a novel simulated scenario that mimics the real world, where our model outperforms other SOTA.

关键词： Face 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 << < 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：