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

50,480 篇 会议
1,421 册 图书
1,042 篇 期刊文献
1 篇 学位论文

馆藏范围

52,941 篇 电子文献
3 种 纸本馆藏

日期分布

学科分类号

31,809 篇 工学
- 24,802 篇 计算机科学与技术...
- 12,567 篇 软件工程
- 5,155 篇 光学工程
- 4,748 篇 电气工程
- 4,432 篇 信息与通信工程
- 4,257 篇 机械工程
- 3,950 篇 控制科学与工程
- 2,474 篇 生物工程
- 1,729 篇 生物医学工程（可授...
- 1,580 篇 仪器科学与技术
- 1,310 篇 电子科学与技术（可...
- 793 篇 化学工程与技术
- 697 篇 安全科学与工程
- 541 篇 交通运输工程
- 379 篇 建筑学
- 331 篇 土木工程
11,837 篇 理学
- 6,435 篇 物理学
- 5,405 篇 数学
- 2,761 篇 生物学
- 1,911 篇 统计学（可授理学、...
- 797 篇 化学
- 669 篇 系统科学
5,303 篇 医学
- 5,095 篇 临床医学
- 729 篇 基础医学(可授医学...
- 459 篇 药学(可授医学、理...
3,345 篇 管理学
- 1,951 篇 图书情报与档案管...
- 1,533 篇 管理科学与工程(可...
- 479 篇 工商管理
720 篇 艺术学
- 718 篇 设计学（可授艺术学...
428 篇 法学
- 401 篇 社会学
298 篇 农学
197 篇 教育学
163 篇 经济学
63 篇 文学
49 篇 军事学

主题

17,384 篇 computer vision
9,016 篇 pattern recognit...
4,195 篇 training
3,814 篇 feature extracti...
3,134 篇 cameras
2,870 篇 computational mo...
2,790 篇 image segmentati...
2,621 篇 visualization
2,573 篇 shape
2,533 篇 face recognition
2,171 篇 robustness
2,123 篇 computer science
1,972 篇 object detection
1,959 篇 computer archite...
1,878 篇 layout
1,852 篇 object recogniti...
1,802 篇 three-dimensiona...
1,725 篇 neural networks
1,708 篇 humans
1,691 篇 image recognitio...

机构

165 篇 univ chinese aca...
144 篇 tsinghua univers...
136 篇 national laborat...
107 篇 univ sci & techn...
104 篇 zhejiang univers...
100 篇 shanghai jiao to...
95 篇 microsoft resear...
94 篇 university of sc...
85 篇 zhejiang univ pe...
84 篇 shanghai ai lab ...
74 篇 school of comput...
69 篇 computer vision ...
68 篇 peking univ peop...
68 篇 chinese acad sci...
65 篇 chinese univ hon...
63 篇 institute of inf...
62 篇 google res mount...
61 篇 univ oxford oxfo...
59 篇 univ toronto on
57 篇 swiss fed inst t...

作者

91 篇 van gool luc
87 篇 umapada pal
76 篇 zhang lei
64 篇 lee seong-whan
50 篇 vittorio murino
42 篇 yang yi
34 篇 nassir navab
33 篇 li xin
33 篇 jie yang
32 篇 liu yang
31 篇 escalera sergio
31 篇 loy chen change
30 篇 ling haibin
30 篇 h. bischof
29 篇 zhou jie
29 篇 vasconcelos nuno
29 篇 jan-michael frah...
29 篇 hanqing lu
28 篇 blumenstein mich...
27 篇 jia yunde

语言

51,872 篇 英文
835 篇 其他
241 篇 中文
22 篇 土耳其文
5 篇 西班牙文
2 篇 日文
2 篇 葡萄牙文
2 篇 俄文

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

共 52944 条记录，以下是4511-4520 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：

Emotion Detection in Social Robotics: Empath-Obscura - An Ensemble Approach with Novel Face Augmentation Using SPIGA 17

Emotion Detection in Social Robotics: Empath-Obscura - An En...

引用

7th ieee International conference on Robotic Computing (IRC)

作者： Dasgupta, Debajyoti Mondal, Arijit Chakrabarti, Partha P. Indian Inst Technol Kharagpur Comp Sci & Engn Kharagpur India Indian Inst Technol Patna Comp Sci & Engn Patna India

ISBN: (纸本)9798350395747

Emotion recognition is a key component of human-computer interaction in social robotics. In this paper, we present Empath-Obscura, an innovative ensemble model designed to detect emotions in obfuscated faces. The model combines the cutting-edge object detection models YOLO V5 and V8 with the well-established Poster++ facial emotion recognition model. A significant contribution of this work is the development of a novel data augmentation technique that utilizes SPIGA, a shape-preserving facial landmark detection model, to selectively obscure facial features. This approach enhances the model's robustness against partially hidden facial expressions, improving the performance of the overall model by 13.18%. Empath-Obscura is rigorously validated on the FER-2013 dataset, which is well-suited for this study due to its representation of low-resolution and poor-quality facial images. A manually obfuscated and annotated test set further ensures accurate evaluation. The ensemble model achieved a remarkable accuracy of 69.3%, outperforming the individual models. The results presented in this paper, along with the innovation in our ensemble and data augmentation techniques, offer a significant contribution to the fields of social robotics and emotion recognition. This work provides researchers and practitioners with a robust and reliable tool for emotion detection from obfuscated faces, contributing to advancements in human-computer interaction for social robotics.

关键词： Emotion recognition Social Robotics Data Augmentation Obfuscated Faces Ensemble Model Human-computer Interaction computer vision

来源：评论

学校读者我要写书评

暂无评论

Cross Modal Focal Loss for RGBD Face Anti-Spoofing

Cross Modal Focal Loss for RGBD Face Anti-Spoofing

引用

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

作者： George, Anjith Marcel, Sebastien Idiap Res Inst Rue Marconi 19 CH-1920 Martigny Switzerland

ISBN: (纸本)9781665445092

Automatic methods for detecting presentation attacks are essential to ensure the reliable use of facial recognition technology. Most of the methods available in the literature for presentation attack detection (PAD) fails in generalizing to unseen attacks. In recent years, multi-channel methods have been proposed to improve the robustness of PAD systems. Often, only a limited amount of data is available for additional channels, which limits the effectiveness of these methods. In this work, we present a new framework for PAD that uses RGB and depth channels together with a novel loss function. The new architecture uses complementary information from the two modalities while reducing the impact of ovetfitting. Essentially, a cross-modal focal loss function is proposed to modulate the loss contribution of each channel as a function of the confidence of individual channels. Extensive evaluations in two publicly available datasets demonstrate the effectiveness of the proposed approach.

关键词： computer vision Face recognition Computational modeling computer architecture Robustness

来源：评论

学校读者我要写书评

暂无评论

Smart Home Security System Using Face recognition Based on IoT- CNN 2

Smart Home Security System Using Face Recognition Based on I...

引用

2nd International conference on Information Technology Research and Innovation, ICITRI 2023

作者： Febriantono, M. Aldiki Zuhair, Alvin Khaeruddin School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia University of Islam Blitar Electrical Engineering Department Blitar Indonesia University of Muhammadiyah Malang Diploma III Electronic Technology Vocational Study Program Malang Indonesia

ISBN: (纸本)9798350324945

Home security is a crucial aspect that requires careful attention, particularly when it comes to addressing theft concerns. Hence, implementing smart door technology equipped with facial recognition holds promising potential for enhancing home security. This study aims to develop a more secure and regulated home entry system by leveraging Internet of Things (IoT) technology and Machine Learning computer vision for facial recognition. The system integrates IoT devices, such as cameras and automatic doors, wherein facial image data is captured by the camera and processed using the Convolutional Neural Network (CNN) algorithm to identify individuals. Once an individual is recognized, the system grants access to the home through an automated door. By relying on facial features, the system effectively restricts unauthorized access and safeguards homes against theft risks. Therefore, the advancement of a safer and more controlled home entry system utilizing IoT technology and Machine Learning computer vision holds tremendous benefits for homeowners. © 2023 ieee.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Towards Understanding Personality Expression via Body Motion

Towards Understanding Personality Expression via Body Motion

引用

ieee conference on Virtual Reality and 3D User Interfaces (VR)

作者： Sonlu, Sinan Dogan, Yalim Erguzen, Arcin Ulku Unalan, Musa Ege Demirci, Serkan Durupinar, Funda Gudukbay, Ugur Bilkent Univ Bilkent Turkiye Univ Massachusetts Boston MA USA

ISBN: (数字)9798350374490

ISBN: (纸本)9798350374490;9798350374506

This work addresses the challenge of data scarcity in personality-labeled datasets by introducing personality labels to clips from two open datasets, ZeroEGGS and Bandai, which provide diverse fullbody animations. To this end, we present a user study to annotate short clips from both sets with labels based on the Five-Factor Model (FFM) of personality. We chose features informed by Laban Movement Analysis (LMA) to represent each animation. These features then guided us to select the samples of distinct motion styles to be included in the user study, obtaining high personality variance and keeping the study duration and cost viable. Using the labeled data, we then ran a correlation analysis to find features that indicate high correlation with each personality dimension. Our regression analysis results indicate that highly correlated features are promising in accurate personality estimation. We share our early findings, code, and data publicly.

关键词： Computing methodologies Artificial intelligence computer vision Activity recognition and understanding Computing methodologies computer graphics Animation Motion processing

来源：评论

学校读者我要写书评

暂无评论

Fair Feature Distillation for Visual recognition

Fair Feature Distillation for Visual Recognition

引用

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

作者： Jung, Sangwon Lee, Donggyu Park, Taeeon Moon, Taesup Sungkyunkwan Univ Dept Elect & Comp Engn Suwon South Korea Seoul Natl Univ Dept Elect & Comp Engn Seoul South Korea

ISBN: (纸本)9781665445092

Fairness is becoming an increasingly crucial issue for computer vision, especially in the human-related decision systems. However, achieving algorithmic fairness, which makes a model produce indiscriminative outcomes against protected groups, is still an unresolved problem. In this paper, we devise a systematic approach which reduces algorithmic biases via feature distillation for visual recognition tasks, dubbed as MMD-based Fair Distillation (MFD). While the distillation technique has been widely used in general to improve the prediction accuracy, to the best of our knowledge, there has been no explicit work that also tries to improve fairness via distillation. Furthermore, We give a theoretical justification of our MFD on the effect of knowledge distillation and fairness. Throughout the extensive experiments, we show our MFD significantly mitigates the bias against specific minorities without any loss of the accuracy on both synthetic and real-world face datasets.

关键词： Visualization computer vision Systematics Computational modeling Face recognition Predictive models Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

ADAS: A Direct Adaptation Strategy for Multi-Target Domain Adaptive Semantic Segmentation

ADAS: A Direct Adaptation Strategy for Multi-Target Domain A...

引用

2022 ieee/CVF conference on computer vision and pattern recognition, CVPR 2022

作者： Lee, Seunghun Choi, Wonhyeok Kim, Changjae Choi, Minwoo Im, Sunghoon Dgist Department of Electrical Engineering and Computer Science Daegu Korea Republic of

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

In this paper, we present a direct adaptation strategy (ADAS), which aims to directly adapt a single model to multiple target domains in a semantic segmentation task without pretrained domain-specific models. To do so, we design a multi-target domain transfer network (MTDT-Net) that aligns visual attributes across domains by transferring the domain distinctive features through a new target adaptive denormalization (TAD) module. Moreover, we propose a bi-directional adaptive region selection (BARS) that reduces the attribute ambiguity among the class labels by adaptively selecting the regions with consistent feature statistics. We show that our single MTDT-Net can synthesize visually pleasing domain transferred images with complex driving datasets, and BARS effectively filters out the unnecessary region of training images for each target domain. With the collaboration of MTDT-Net and BARS, our ADAS achieves state-of-the-art performance for multi-target domain adaptation (MTDA). To the best of our knowledge, our method is the first MTDA method that directly adapts to multiple domains in semantic segmentation. © 2022 ieee.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Exploring the Effect of Adversarial Attacks on Deep Learning Architectures for X-Ray Data

Exploring the Effect of Adversarial Attacks on Deep Learning...

引用

ieee Applied Imagery pattern recognition Workshop (AIPR)

作者： Bankole-Hameed, Ilyas Parikh, Arav Harguess, Josh Mitre Corp Mclean VA 22102 USA

ISBN: (纸本)9781665477291

As artificial intelligent models continue to grow in their capacity and sophistication, they are often trusted with very sensitive information. In the sub-field of adversarial machine learning, developments are geared solely towards finding reliable methods to systematically erode the ability of artificial intelligent systems to perform as intended. These techniques can cause serious breaches of security, interruptions to major systems, and irreversible damage to consumers. Our research evaluates the effects of various white box adversarial machine learning attacks on popular computer vision deep learning models leveraging a public X-ray dataset from the National Institutes of Health (NIH). We make use of several experiments to gauge the feasibility of developing deep learning models that are robust to adversarial machine learning attacks by taking into account different defense strategies, such as adversarial training, to observe how adversarial attacks evolve over time. Our research details how a variety white box attacks effect different components of InceptionNet, DenseNet, and ResNeXt and suggest how the models can effectively defend against these attacks.

关键词： adversarial machine learning ML attacks baseline computer vision AI security

来源：评论

学校读者我要写书评

暂无评论

MetricOpt: Learning to Optimize Black-Box Evaluation Metrics

MetricOpt: Learning to Optimize Black-Box Evaluation Metrics

引用

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

作者： Huang, Chen Zhai, Shuangfei Guo, Pengsheng Susskind, Josh Apple Inc Cupertino CA 95014 USA

ISBN: (纸本)9781665445092

We study the problem of directly optimizing arbitrary non-differentiable task evaluation metrics such as misclassification rate and recall. Our method, named MetricOpt, operates in a black-box setting where the computational details of the target metric are unknown. We achieve this by learning a differentiable value function, which maps compact task-specific model parameters to metric observations. The learned value function is easily pluggable into existing optimizers like SGD and Adam, and is effective for rapidly finetuning a pre-trained model. This leads to consistent improvements since the value function provides effective metric supervision during finetuning, and helps to correct the potential bias of loss-only supervision. MetricOpt achieves state-of-the-art performance on a variety of metrics for (image) classification, image retrieval and object detection. Solid benefits are found over competing methods, which often involve complex loss design or adaptation. MetricOpt also generalizes well to new tasks and model architectures.

关键词： Measurement Computational modeling Image retrieval computer architecture Object detection Solids pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Repetitive Activity Counting by Sight and Sound

Repetitive Activity Counting by Sight and Sound

引用

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

作者： Zhang, Yunhua Shao, Ling Snoek, Cees G. M. Univ Amsterdam Amsterdam Netherlands Incept Inst Artificial Intelligence Abu Dhabi U Arab Emirates

ISBN: (纸本)9781665445092

This paper strives for repetitive activity counting in videos. Different from existing works, which all analyze the visual video content only, we incorporate for the first time the corresponding sound into the repetition counting process. This benefits accuracy in challenging vision conditions such as occlusion, dramatic camera view changes, low resolution, etc. We propose a model that starts with analyzing the sight and sound streams separately. Then an audiovisual temporal stride decision module and a reliability estimation module are introduced to exploit cross-modal temporal interaction. For learning and evaluation, an existing dataset is repurposed and reorganized to allow for repetition counting with sight and sound. We also introduce a variant of this dataset for repetition counting under challenging vision conditions. Experiments demonstrate the benefit of sound, as well as the other introduced modules, for repetition counting. Our sight-only model already outperforms the state-of-the-art by itself, when we add sound, results improve notably, especially under harsh vision conditions. The code and datasets are available at https://***/xiaobai1217/RepetitionCounting.

关键词： Visualization computer vision Analytical models Codes Estimation Cameras pattern recognition

来源：评论

学校读者我要写书评

暂无评论

TextOCR: Towards large-scale end-to-end reasoning for arbitrary-shaped scene text

TextOCR: Towards large-scale end-to-end reasoning for arbitr...

引用

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

作者： Singh, Amanpreet Peng, Guan Toh, Mandy Huang, Jing Galuba, Wojciech Hassner, Tal Facebook AI Res Menlo Pk CA 94025 USA

ISBN: (纸本)9781665445092

A crucial component for the scene text based reasoning required for TextVQA and TextCaps datasets involve detecting and recognizing text present in the images using an optical character recognition (OCR) system. The current systems are crippled by the unavailability of ground truth text annotations for these datasets as well as lack of scene text detection and recognition datasets on real images disallowing the progress in the field of OCR and evaluation of scene text based reasoning in isolation from OCR systems. In this work, we propose TextOCR, an arbitrary-shaped scene text detection and recognition with 900k annotated words collected on real images from TextVQA dataset. We show that current state-of-the-art text-recognition (OCR) models fail to perform well on TextOCR and that training on TextOCR helps achieve state-of-the-art performance on multiple other OCR datasets as well. We use a TextOCR trained OCR model to create PixelM4C model which can do scene text based reasoning on an image in an end-to-end fashion, allowing us to revisit several design choices to achieve new state-of-the-art performance on TextVQA dataset.

关键词： Training computer vision Image recognition Text recognition Optical feedback Optical imaging Cognition

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 << < 448 449 450 451 452 453 454 455 456 457 > >>

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：