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

50,499 篇 会议
1,420 册 图书
1,018 篇 期刊文献
1 篇 学位论文

馆藏范围

52,935 篇 电子文献
3 种 纸本馆藏

日期分布

学科分类号

31,784 篇 工学
- 24,773 篇 计算机科学与技术...
- 12,555 篇 软件工程
- 5,155 篇 光学工程
- 4,739 篇 电气工程
- 4,428 篇 信息与通信工程
- 4,255 篇 机械工程
- 3,950 篇 控制科学与工程
- 2,475 篇 生物工程
- 1,729 篇 生物医学工程（可授...
- 1,579 篇 仪器科学与技术
- 1,305 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
11,835 篇 理学
- 6,437 篇 物理学
- 5,401 篇 数学
- 2,762 篇 生物学
- 1,910 篇 统计学（可授理学、...
- 797 篇 化学
- 668 篇 系统科学
5,301 篇 医学
- 5,094 篇 临床医学
- 727 篇 基础医学(可授医学...
- 459 篇 药学(可授医学、理...
3,346 篇 管理学
- 1,951 篇 图书情报与档案管...
- 1,534 篇 管理科学与工程(可...
- 480 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

17,316 篇 computer vision
8,990 篇 pattern recognit...
4,198 篇 training
3,815 篇 feature extracti...
3,129 篇 cameras
2,870 篇 computational mo...
2,774 篇 image segmentati...
2,620 篇 visualization
2,551 篇 shape
2,538 篇 face recognition
2,166 篇 robustness
2,118 篇 computer science
1,969 篇 object detection
1,960 篇 computer archite...
1,859 篇 layout
1,841 篇 object recogniti...
1,802 篇 three-dimensiona...
1,726 篇 neural networks
1,704 篇 humans
1,686 篇 image recognitio...

机构

165 篇 univ chinese aca...
144 篇 tsinghua univers...
135 篇 national laborat...
107 篇 univ sci & techn...
104 篇 zhejiang univers...
100 篇 shanghai jiao to...
94 篇 university of sc...
94 篇 microsoft resear...
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...
28 篇 blumenstein mich...
28 篇 hanqing lu
27 篇 jia yunde

语言

50,671 篇 英文
2,031 篇 其他
246 篇 中文
22 篇 土耳其文
4 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 52938 条记录，以下是4151-4160 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：

An improved image segmentation model of FCN based on residual network 4

An improved image segmentation model of FCN based on residua...

引用

4th International conference on computer vision, Image and Deep Learning, CVIDL 2023

作者： Du, Wenchao Yang, Haotian Toe, Teoh Teik School of Computer Science JiangSu University Zhenjiang China NanyangTechnological University NTU Business AI Lab Singapore

ISBN: (纸本)9798350326444

In this paper, the fcn model with Resnet as backbone is used for training and testing on voc2007 dataset. Twenty categories were trained, tested, and trained for around of about 10,000 pictures. There cognition and segmentation ofimages are realized. The overall recognition rate reaches 92.6%. The overall IoU reaches 68.3%, which is higher than the 5.6% of FCN-8s in theoriginal paper. We have adjusted the network structure of Resnet and improved the algorithm to achieve the accuracy of identification and segmentation with less time cost. The weight of thisalgorithm after training can be applied to specificoccasions of image recognition or object detection. © 2023 ieee.

关键词： Image recognition

来源：评论

学校读者我要写书评

暂无评论

Kullback–Leibler Distance-Based Fuzzy K-Plane Clustering Approach for Noisy Human Brain MRI Image Segmentation

Kullback–Leibler Distance-Based Fuzzy K-Plane Clustering Ap...

引用

International conference on computer vision and Machine Intelligence, CVMI 2022

作者： Kumar, Puneet Agrawal, R.K. Kumar, Dhirendra School of Computer & Systems Sciences Jawaharlal Nehru University Delhi India Department of Applied Mathematics Delhi Technological University Delhi India

ISBN: (纸本)9789811978661

MR images are complex as the data distribution of tissues in MR images is non-spherical and overlapping in nature. The fuzzy k-plane clustering method (FkPC) is the most suitable soft clustering method to cluster non-spherical shape data and solve the overlapping problem of MR tissues. Generally, MR images are corrupted with imaging artifacts such as noise and intensity inhomogeneity. The FkPC method performs poor in the presence of noise. In this work, a new objective function for handling noise in the plane-based clustering approach is discussed with application to the MR image segmentation problem. We have utilised Kullback–Leibler (KL) distance measure to dampen the effect of noise in the k-plane clustering approach for the image segmentation problem. The proposed method is termed as KL distance-based fuzzy k-plane clustering (KLFkPC) method. Three publicly available MRI image datasets were utilised in the study to assess the efficiency of the proposed KLFkPC approach. The results are evaluated using a variety of performance metrics that demonstrate the efficacy of the proposed method over the ten existing related methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Interactive Image Processing: Design Of An AI Assisted Human computer Interaction Logic Using Gesture recognition Model Based On Logical Open CV Scheme 2

Interactive Image Processing: Design Of An AI Assisted Human...

引用

2nd ieee International conference on Advances in Information Technology, ICAIT 2024

作者： Rani, A. Jaya Mabel Sujatha, S. Anbunathan, R. Celine Kavida, A. Kumar, L. Vinoth Ahamed, B. Shamreen Department of CSE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India Department of EEE Sri Sairam College of Engineering Karnataka Bangalore India Department of Mathematics SA Engineering College Tamil Nadu Chennai India Department of Physics Veltech Multitech Dr Rangarajan Dr. Sakunthala Engineering College Tamil Nadu Chennai India Department of Information Technology RMK Engineering College Tamil Nadu Chennai India Department of CSE Sathyabama Institute of Science and Technology Tamil Nadu Chennai India

ISBN: (纸本)9798350383867

One method that can recognize hand gestures in real-time video is hand gesture recognition. A specific field of study is used to categorize the hand gesture. One of the difficult tasks in this study involving two main problems is the design of the hand gesture recognition system. The first step is to identify the hand. Making a sign that works for just one hand at a time is another challenge. The focus of this system is on developing a computer vision system that can detect, identify, and understand hand gestures, even when faced with tough circumstances such as variations in scale, orientation, position, and attitude. A variety of gestures, including numerical and sign language ones, must be implemented into this system for the development of this study endeavour to be successful. There are a lot of potential uses for this field, which provides a more organic and easy method for humans to interact with robots and system interfaces without the usage of additional hardware. Therefore, developing systems that can recognize individual human gestures and utilize them to transmit data or operate devices is the major objective of gesture recognition research as it pertains to Human-computer Interaction (HCI). This necessitates real-time gesture identification and lightning-fast, very robust hand detection for vision-based hand gesture interfaces. Using an AI algorithm, this study introduces a solution for real-time gesture detection called the Logical Gesture detection Model (LGRM). It is general enough to be applied in many different kinds of human-computer interactions. To verify that the suggested model is effective, it is cross-validated with the traditional method known as the Cascading Gesture Classification Model (CGCM). © 2024 ieee.

关键词： Gesture recognition

来源：评论

学校读者我要写书评

暂无评论

Detection of Motion Vector-Based Stegomalware in Video Files 1

引用

International conference on computer vision and Machine Intelligence, CVMI 2022

作者： Nair, Sandra V. S. Arun Raj Kumar, P. Department of Computer Science and Engineering National Institute of Technology Calicut Kozhikode India

ISBN: (数字)9789811978678

ISBN: (纸本)9789811978661

Cybercriminals are increasingly using steganography to launch attacks on devices. The cyberattack is more threatening as steganography hides the embedded malware, if any, making it harder to detect by various anti-virus tools. Such malware is called stegomalware. Since video files are larger and have a complex structure, they also have a high capacity for hiding malware. Motion vector (MV)-based steganography techniques do not cause much distortion in video files. Therefore, it remains to be one of the leading video steganography techniques. This paper deals with a lightweight solution for MV-based stegomalware detection in video files. Our model is compatible with state-of-the-art video coding standards having variable macroblock sizes and different motion vector resolutions. The proposed method obtained an accuracy of 95.8% on testing H.264 videos with various embedding rates. The 81-D spatial and temporal features result in the high performance of the proposed model. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Video signal processing

来源：评论

学校读者我要写书评

暂无评论

The Enhancement in Road Safety using Different Image Detection and recognition Techniques: - A State of Art

The Enhancement in Road Safety using Different Image Detecti...

引用

2023 ieee International conference on Device Intelligence, Computing and Communication Technologies, DICCT 2023

作者： Agarwal, Megha Seth, Dambarudhar Srm Ist Computer Science and Engineering Ghaziabad India

ISBN: (纸本)9781665474924

Over the last 10 years, researchers and developers shows a significant evolution in the development of intelligent transport systems (ITS) i.e. self-driving cars. One of the challenging issues that researchers are faced with these systems is the detection and recognition of traffic signs. Using computer vision to identify, detect, and classify objects (such as traffic signs) is a problem that is currently difficult to solve. Traffic signs serve a prominent role in protecting drivers and pedestrians from deadly threats that occur due to accidents. There are more than 4000 accidents occur every day in a country that drops 3% GDP of the nation yearly. There have been numerous studies carried out using computer vision for automatic Traffic Sign Detection and recognition (TSDR) which produced good results. In this paper, the author studied various object detection models. © 2023 ieee.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Baxter Robot Shape Feature recognition Algorithm Based on Machine vision 2

Baxter Robot Shape Feature Recognition Algorithm Based on Ma...

引用

2nd ieee International conference on Distributed Computing and Electrical Circuits and Electronics, ICDCECE 2023

作者： Mo, Yi Guangxi Vocational & Technical Institute of Industry Guangxi Nanning China

ISBN: (纸本)9798350347456

With the rapid development of artificial intelligence and computer technology, Machine vision (MV) technology has quietly and deeply affected all aspects of our lives. At the same time, Baxter robots are becoming more and more intelligent and automated. MV technology, especially the shape feature recognition algorithm, is applied to the Baxter robot system to provide technical guarantee for accurate and real-time target feature recognition. Based on the subject of "Baxter Robot Shape Feature recognition Algorithm Based on MV", this paper focuses on the study of shape feature recognition technology. This paper takes Baxter robot as an example to study the key technology of shape feature recognition when the target in the environment is known. This paper designs the Baxter robot vision system, analyzes the system's workflow and functions, and introduces the Baxter robot system modules and related algorithms. In this paper, the algorithm is used to test the shape characteristics of the target object. The results show that the average recognition accuracy rate is 94.37%, and the running time is 11.97ms. From the specific results of target object shape feature detection, the Baxter robot shape feature recognition algorithm based on machine vision achieves real-time and high accuracy of target object shape feature recognition, and has good stability. In practical applications, compared to traditional shape feature recognition algorithms, the Baxter robot shape feature recognition algorithm based on machine vision is more feasible and can effectively assist people in completing specific tasks and targets for shape feature recognition in practical applications. © 2023 ieee.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Enhancing Human Action recognition in Videos through Dense-Level Features Extraction and Optimized Long Short-Term Memory 7

Enhancing Human Action Recognition in Videos through Dense-L...

引用

7th International conference on Electronics, Communications, and Control Engineering (ICECC)

作者： Hassan, Najmul Miah, Abu Saleh Musa Shin, Jungpil Univ Aizu Dept Comp Sci & Engn Aizu Wakamatsu Fukushima Japan

ISBN: (纸本)9798350367546;9798350367195

Human action recognition (HAR) in videos is a field currently receiving considerable attention in computer vision and pattern recognition. While numerous researchers have been working on developing a HAR system, they still face challenges in achieving satisfactory performance in video-based activity recognition systems. Video-based action recognition poses a significant research challenge due to temporal feature dependency. Currently, there is a demand to develop dynamic HAR systems that can deliver high-performance accuracy with generalizability. In order to address these shortcomings, we propose a dynamic HAR system by leveraging a deep learning (DL) based temporal feature extraction approach. In this process, we initially use the DL-based DenseNet121 model to extract frame-level dense features. Subsequently, we feed these features into an optimized Long Short-Term Memory (LSTM) network to learn dependencies and process data for optimal predictions. Furthermore, during the testing phase, an iterative fine-tuning procedure is incorporated to update the high parameters of the trained system, aiming to achieve optimal results. Experiments conducted on a benchmark dataset demonstrate superior performance in terms of both accuracy and losses compared to existing methods.

关键词： Human Action recognition (HAR) Human-computer Interaction (HCI) Deep Learning DenseNet121 LSTM

来源：评论

学校读者我要写书评

暂无评论

Hand Multimodal recognition Based on Adaptive Multichannel Graph Convolutional Networks 5

Hand Multimodal Recognition Based on Adaptive Multichannel G...

引用

5th ieee International conference on pattern recognition and Machine Learning, PRML 2024

作者： Lai, Xinbo Abdireyim, Alimjan Kasenmu, Reyihanguli Yadikar, Nurbiya Ubul, Kurban School of Computer Science and Technology Xinjiang University Urumqi China Science and Technology Project Service Centre Xinjiang Uighur Autonomous Region Urumqi China School of Information Science and Technology Xinjiang Normal and Higher Polytechnic University Urumqi China

ISBN: (纸本)9798350355925

In the biometrics field, the unimodal biometrics recognition effect cannot meet the requirements for high-performance identity recognition due to its characteristics, such as instability and limitations. Multimodal biometrics combines two or more biometric features to improve the accuracy and security of identification, and combining multiple biometric features can make up for the shortcomings of unimodal biometrics. Aiming at the above problems, this paper proposes a hand multimodal recognition network based on an adaptive multichannel graph convolutional network, which adopts the PageRank centrality fusion method for image fusion of fingerprints, finger veins, and palm veins so that the network takes into account both the feature novelty information and the structural information in the image fusion process. At the same time, we introduce the CBAM attention module in the network to allow the network to adaptively learn important features in channel and spatial dimensions to improve the network's performance. The experimental results show that the recognition accuracy of the method proposed in this paper reaches 99.96%, which has high performance and can be widely used in practical applications. © 2024 ieee.

关键词： Image fusion

来源：评论

学校读者我要写书评

暂无评论

Towards Domain-Specific Explainable AI: Model Interpretation of a Skin Image Classifier using a Human Approach

Towards Domain-Specific Explainable AI: Model Interpretation...

引用

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

作者： Stieler, Fabian Rabe, Fabian Bauer, Bernhard Univ Augsburg Augsburg Germany

ISBN: (纸本)9781665448994

Machine Learning models have started to outperform medical experts in some classification tasks. Meanwhile, the question of how these classifiers produce certain results is attracting increasing research attention. Current interpretation methods provide a good starting point in investigating such questions, but they still massively lack the relation to the problem domain. In this work, we present how explanations of an AI system for skin image analysis can be made more domain-specific. We apply the synthesis of Local Interpretable Model-agnostic Explanations (LIME) with the ABCD-rule, a diagnostic approach of dermatologists, and present the results using a Deep Neural Network (DNN) based skin image classifier.

关键词： Deep learning computer vision Image analysis Computational modeling conferences Skin pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Research on Person Re-Identification Based on Specific Frame Posture Detection 4

Research on Person Re-Identification Based on Specific Frame...

引用

4th ieee International conference on Software Engineering and Artificial Intelligence (SEAI)

作者： Song Fuyao Xu Jie Lan Haoliang Jiangsu Police Inst Nanjing Jiangsu Peoples R China

ISBN: (数字)9798350374346

ISBN: (纸本)9798350374353;9798350374346

With the increasing demand for video surveillance and personal safety, posture-based person re-identification technology has become increasingly important. This paper proposes a method for human posture detection using OpenPose and identifies individuals by utilizing the detected key points. The method first learns the posture features of trained individuals from multiple videos, and then in the test video, it can accurately identify different individuals through posture detection even if the facial and clothing features of the individuals change. Experimental results show that the method has a high recognition accuracy and robustness in different scenarios.

关键词： person re-identification OpenPose computer vision

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 << < 412 413 414 415 416 417 418 419 420 421 > >>

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：