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

18,409 篇 会议
217 册 图书
188 篇 期刊文献

馆藏范围

18,811 篇 电子文献
3 种 纸本馆藏

日期分布

学科分类号

13,438 篇 工学
- 9,747 篇 计算机科学与技术...
- 6,612 篇 软件工程
- 3,603 篇 控制科学与工程
- 2,471 篇 信息与通信工程
- 2,304 篇 电气工程
- 1,741 篇 光学工程
- 1,517 篇 机械工程
- 1,118 篇 生物工程
- 909 篇 电子科学与技术（可...
- 864 篇 生物医学工程（可授...
- 785 篇 仪器科学与技术
- 574 篇 动力工程及工程热...
- 543 篇 交通运输工程
- 513 篇 安全科学与工程
- 499 篇 材料科学与工程（可...
- 454 篇 化学工程与技术
- 349 篇 土木工程
- 335 篇 网络空间安全
5,368 篇 理学
- 2,366 篇 物理学
- 2,288 篇 数学
- 1,231 篇 生物学
- 598 篇 统计学（可授理学、...
- 589 篇 系统科学
- 449 篇 化学
2,423 篇 管理学
- 1,722 篇 管理科学与工程(可...
- 830 篇 图书情报与档案管...
- 687 篇 工商管理
1,096 篇 医学
- 972 篇 临床医学
- 561 篇 基础医学(可授医学...
- 362 篇 药学(可授医学、理...
364 篇 法学
259 篇 经济学
253 篇 农学
218 篇 教育学
64 篇 军事学
25 篇 艺术学
20 篇 文学
3 篇 哲学

主题

1,582 篇 computer vision
370 篇 deep learning
314 篇 computer archite...
282 篇 cameras
255 篇 object detection
253 篇 computational mo...
237 篇 control systems
236 篇 computer science
220 篇 image segmentati...
211 篇 feature extracti...
209 篇 internet of thin...
187 篇 access control
173 篇 machine vision
158 篇 neural networks
137 篇 artificial intel...
133 篇 face recognition
130 篇 process control
130 篇 real-time system...
129 篇 data mining
128 篇 support vector m...

机构

47 篇 chitkara univers...
46 篇 school of comput...
43 篇 school of contro...
29 篇 maharishi school...
24 篇 karnataka bangal...
21 篇 school of comput...
19 篇 maharishi school...
17 篇 chitkara univers...
17 篇 college of compu...
15 篇 university of ch...
15 篇 school of comput...
14 篇 south china univ...
14 篇 dept. of compute...
14 篇 department of co...
14 篇 chitkara univers...
14 篇 college of compu...
13 篇 school of comput...
12 篇 school of comput...
12 篇 centre of interd...
12 篇 school of comput...

作者

19 篇 wang lei
18 篇 li yang
17 篇 wang wei
16 篇 yang yang
14 篇 liu yang
13 篇 wang hui
13 篇 ryszard tadeusie...
13 篇 marcin korytkows...
12 篇 wang ping
12 篇 wang jian
12 篇 sato jun
12 篇 jacek m. zurada
11 篇 zhang tao
11 篇 sakaue fumihiko
11 篇 zhang lei
11 篇 huang tinglei
11 篇 liu lei
10 篇 lei wang
10 篇 li xin
10 篇 wang jing

语言

16,844 篇 英文
1,863 篇 其他
133 篇 中文
16 篇 俄文
7 篇 西班牙文
2 篇 法文
2 篇 土耳其文

检索条件"任意字段=Proceedings of the 3rd International Conference on Control and Computer Vision"

共 18814 条记录，以下是851-860 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：

A Compensation Method for Lost Trajectories of ORB-SLAM3 with DROID-VO 3

A Compensation Method for Lost Trajectories of ORB-SLAM3 wit...

引用

3rd international conference on computer, control and Robotics, ICCCR 2023

作者： Liu, Kairong Fan, Yong Su, Jianmei Wu, Ling Zhang, Kexin School of Computer Science and Technology Southwest University of Science and Technology Sichuan China

ISBN: (纸本)9781665492126

Under extreme conditions such as pure rotation, motion blur and poor texture, ORB-SLAM3 cannot perform pose estimation well which leads to trajectory loss inevitably. In this paper, we present a robust compensation method which uses DROID-VO to generate lost trajectories and inserts them into ORB-SLAM3 accurately. Experimental results on EuRoC, Tartanair and TUM-RGBD datasets indicate that the proposed method achieves hizher coverage and can adapt to more conditions. © 2023 IEEE.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

Intelligent Machine Learning Framework for Classification of Vehicular Traffic in Internet of Vehicles 3

Intelligent Machine Learning Framework for Classification of...

引用

3rd international conference on Power Electronics and IoT Applications in Renewable Energy and its control, PARC 2024

作者： Tripathy, Biswajit Tripathy, Subhranshu Sekhar Bebortta, Sujit Mukherjee, Tanmay Ravenshaw University Departmenet of Computer Science Cuttack75303 India KIIT Deemed to Be University School of Computer Engineering Bhubaneswar751024 India University Department of Computer Science and Engineering Bhubaneswar751030 India

ISBN: (纸本)9798350309409

In a world that is always changing due to population growth, it is difficult to forecast how routes will behave in the future, especially with regard to traffic. In this work, Traci was used to generate traffic-related data in a real-world setting, including waiting periods, coordinates, speed, and displacement. After that, cars were categorized according to how long they took to wait, and performance was examined using a variety of machine learning methods, such as Random Forest (RF), K-Nearest Neighbor (KNN), Support Vector Machine (SVM), and K-means. The RF algorithm fared better than other algorithms, according to empirical studies, in estimating waiting times and evaluating traffic conditions. After that, the study used the Rapidly Exploring Random Tree (RRT) algorithm, a path-planning and simplification technique, to find vehicle travel paths that would not cause collisions. By decreasing wait times and improving customer satisfaction, this strategy aims to optimize journey routes and cut related expenses. Drones are used in the proposed system, and base stations and ad hoc networks work together to improve overall performance. © 2024 IEEE.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

Waysides Inspection Using Wayside Processing Imaging and Deep Learning 3

Waysides Inspection Using Wayside Processing Imaging and Dee...

引用

3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Thillaikkarasi, R. Yaseen, M. Mohamed Rameshbabu, R. Prabhakaran, Radha Kesavan, R. Jose Anand, A. Salem College of Engineering and Technology Department of Ece Tamil Nadu Salem636111 India Kcg College of Technology Department of Ece Tamil Nadu Chennai600097 India Vsb Engineering College Department of Ece Tamil Nadu Puduvoyal639117 India Institute of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Science Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350322842

Advances in deep learning techniques have made computer vision tasks more accurate and faster by relying on convolutional neural networks and more powerful hardware. In industry, automatic inspection supported by these methods is capable of offering constant maintenance and avoiding accidents on railways. Thus, this work proposes the application of deep learning and image processing methods to perform the automatic inspection of wheel sets in train cars. More specifically, the size of the wheel and the thickness of the bandage are measured, in addition to locating the bearings' fixation screws. The constructed neural network performs semantic segmentation on photographs provided by the mining company Vale. Using a U-Net architecture, with ResNet50 as a backbone, the network was able to reach 92.50% in mIoU and 97.52% in mPA, metrics adopted to evaluate this proposal. The post-processing step recovered the screws and improved the evaluation metrics, indicating the success of the proposed inspection. © 2023 IEEE.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Safety Helmet Detection Using YOLO V8 3

Safety Helmet Detection Using YOLO V8

引用

3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Patel, Krunal Patel, Vrajesh Prajapati, Vikrant Chauhan, Darshak Haji, Adil Degadwala, Sheshang Sigma University Department of Civil Engineering Gujarat Vadodara India Sigma University Department of Computer Engineering Gujarat Vadodara India

ISBN: (纸本)9798350322842

Ensuring safety in the workplace is crucial to the wellbeing of workers and the success of organizations. One essential aspect of workplace safety is the use of safety helmets in hazardous environments. Safety helmets protect workers from head injuries caused by falling objects, electric shocks, and other hazards. In recent years, computer vision-based safety helmet detection systems have gained popularity as a means of ensuring compliance with safety regulations and reducing accidents. This study proposes a safety helmet detection system based on the You Only Look Once (YOLO) V8 algorithm, which is a state-of-the-art object detection algorithm that has shown superior performance in detecting small objects in real-time. The proposed system involves training the YOLO V8 algorithm on a dataset of images containing workers with and without safety helmets. The dataset was carefully curated to include various lighting conditions, camera angles, and helmet types. The trained model was then evaluated on a separate test set to measure its performance. Experimental results demonstrate that the proposed approach achieves high accuracy in detecting safety helmets, with an average precision of 0.99 and a recall of 0.99. The model also demonstrated robustness to variations in lighting and camera angles, making it suitable for real-world deployment. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Semantic Image Synthesis with vision Graph Neural Network 3

Semantic Image Synthesis with Vision Graph Neural Network

引用

3rd international conference on computer Graphics, Image, and Virtualization, ICCGIV 2023

作者： Xu, Zhihong Qian, Xiaozhao Wang, Peng Department of Data Science and Management Alibaba Business School Hangzhou Normal University Hangzhou China

ISBN: (纸本)9781510671720

Semantic image synthesis aims to generate realistic images from semantic label maps. Current generative adversarial network models still struggle with understanding visual information with irregular topological structures because they rely on convolutional neural networks, which interpret semantic label map as grid structures. In this work, we propose a vision GNN Generative Adversarial Network (VG-GAN). In our redesigned generator, the input semantic label map is embedded in patches and then converted into a graph structure. We use graph neural networks on the constructed graph to learn the complex interrelationships in the graph structure. Experimental results show that our proposed method generates images with irregular and complex objects that appear more realistic and perform better than state-of-the-art methods. © 2023 SPIE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

STANet: a Spatial-Temporal Aggregation Network for Video Deraining 3

STANet: a Spatial-Temporal Aggregation Network for Video Der...

引用

3rd international conference on Neural Networks, Information and Communication Engineering, NNICE 2023

作者： Li, Bin Yan, Tao He, Weijiang Zhu, Xiangjie School of Artificial Intelligence and Computer Science Jiangnan University Jiangsu Wuxi China

ISBN: (纸本)9798350335972

Rain can significantly reduce the visibility of a scene, which hinders a lot of computer vision systems, such as outdoor surveillance and autonomous driving. Comparing with single images, rainy videos can record abundant spatial-temporal information of target scenes, which have tremendous advantages in a wide of computer vision tasks. However, how to effectively extract and aggregate spatial representations and temporal correlations of a video sequence for rain removal is a nontrivial task. In this paper, we propose a novel spatial-temporal aggregation network, called STANet, for video deraining. It can learn the temporal correlations and spatial representations of consecutive rainy frames, and then adaptively aggregate them through an iterative attention mechanism. Finally, a refinement sub-network is proposed to further remove the remaining rain streaks and generate clean rain-free video. Extensive experiments demonstrate that our proposed network outperforms state-of-the-art methods by delivering excellent results in both quality and speed. © 2023 IEEE.

关键词： Aggregates

来源：评论

学校读者我要写书评

暂无评论

A Position and Attitude Precise control Method of Electric-Assisted Transfer Vehicle 3

A Position and Attitude Precise Control Method of Electric-A...

引用

3rd international conference on Mechatronics and Automation Technology, ICMAT 2024

作者： Xu, Yuefei Jia, Fengru Xu, Yinfei Meng, Haojie Shen, Jinggui Wang, Xiu Hu, Yueli Liu, Xuqiang Liu, Mingjie Hangzhou Power Equipment Manufacturing Co. Ltd. Hangzhou311100 China School of Automation Hangzhou Dianzi University Hangzhou310018 China

ISBN: (纸本)9781643685649

This paper presents a control method for adjusting the position of an electrical-assisted transfer vehicle in the context of substation auxiliary operation platforms. The proposed method integrates robotics, automatic control technology, and network communication technology to achieve precise attitude control and effective position adjustments. The control model is based on a two-wheel differential model, with a focus on posture adjustment strategies and dual-loop control. The paper also discusses the use of binocular vision for detecting target information and the 3D reconstruction process. The effectiveness of the proposed method is verified through a specific example, demonstrating its ability to meet error threshold requirements. © 2024 The Authors.

关键词： Binocular vision

来源：评论

学校读者我要写书评

暂无评论

Aircraft Target Detection Based on Attention Mechanism and Faster R-CNN 3

Aircraft Target Detection Based on Attention Mechanism and F...

引用

3rd international conference on computer vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Lai, Yunqian Dong, Xinyue Tang, Yuan Chengdu University of Technology College of Computer and Network Security Chengdu China

ISBN: (纸本)9781665459112

Aircraft, as a special strategic target, has high value in both civil and military use, and it is especially important to achieve intelligent scientific aircraft target detection compared to traditional methods. Therefore, an aircraft detection method based on attention mechanism and Faster R-CNN target detection algorithm is proposed in this paper. The RSOD dataset is selected, and the VOC format dataset is used for pre-processing and data enhancement. The Faster R-CNN model is constructed, which uses ResNet50 as the backbone network for feature extraction and also adds the attention mechanism in the backbone network;the region proposal is obtained after convolving the feature extraction results using the RPN(Region Proposal Network);the prediction results are finally obtained by pooling using ROI Pooling. The experimental results show that the model can have good recognition effect and provide help for the intelligent recognition of aircraft. © 2022 IEEE.

关键词： Image recognition

来源：评论

学校读者我要写书评

暂无评论

Research on a control Method of DC Speed Regulating Electric Energy Vehicle Based on Neural Network 3

Research on a Control Method of DC Speed Regulating Electric...

引用

3rd international conference on computer vision, Image and Deep Learning and international conference on computer Engineering and Applications, CVIDL and ICCEA 2022

作者： Chen, Wanxin Lan, Wenyu Li, Xunrui School of Electric Power Engineering Nanjing Institute of Technology Nanjing China Chongqing University of Posts and Telecommunications School of Automation School of Industrial Internet Chongqing China

ISBN: (纸本)9781665459112

With the aggravation of the global shortage of petroleum resources, the problem of optimizing the motor efficiency of new energy vehicles is imminent. Considering that it is difficult to set the speed controller parameters in the traditional brushless DC motor speed system control, and the traditional control has the disadvantages of lag and low-speed prediction accuracy due to the current state feedback signal, a control algorithm based on fuzzy BP neural network is proposed for the energy vehicle. In this paper, based on the mathematical model of DC motor, the space equation is established, the control ability of DC motor is analyzed. Meanwhile, the control theory of BP neural network algorithm is applied to design the related algorithm of a double closed-loop DC speed regulation system. Finally, the motor simulation experiment platform is built through Simulation, and the control effect of the SCM control model is tested through online debugging of Proteus and Keil. The control chip uses AT89C52, the driver module uses L298N chip, and the display module uses LCD1602 display screen. The results show that under the same input conditions, the fuzzy BP network combined with the double closed-loop PID control method has the advantage of significantly reducing the response time and no overshoot. When the disturbance occurs, the time for the system to return to steady-state is short, so it has a high guiding value in engineering. © 2022 IEEE.

关键词： Electric machine control

来源：评论

学校读者我要写书评

暂无评论

A Review of IoT-Driven Innovations in Supply Chain Management 3

A Review of IoT-Driven Innovations in Supply Chain Managemen...

引用

3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Chandankhede, Arpit Gourshettiwar, Palash Faculty of Engineering and Technology Department of Artificial Intelligence and Data Science Sawangi Meghe Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Computer Science and Engineering Sawangi Meghe Maharashtra Wardha442001 India

ISBN: (纸本)9798331509675

Supply Chain Management (SCM) worldwide makes major advancements through the Internet of Things (IoT) by enabling real-time monitoring and prediction analytics and automatic decision capabilities in worldwide deliver chains. Through IoT technology integration with Artificial Intelligence (AI) and blockchain and cloud computing the supply chain solves major operational problems including monitoring difficulties and waste reduction and regulatory compliance requirements and operation leadership deficits. The implementation of IoT for supply chain management encounters major adoption barriers from high installation costs combined with security risks and operability complications as well as limited scalability capacity that affects especially small to medium enterprises (SMEs) and developing markets. The evaluation paper examines the shifting impact of IoT in supply chain management which enhances performance metrics and brings greater clarity and strengthens supply chain resilience. A scientist studied existing papers and case studies to reveal several essential advantages which include better inventory management, predictive analysis systems and more effective supply-chain collaborations. The analysis emphasizes effective solutions for security privacy and moral and environmental issues to guarantee sustainable expanded IoT adoption. This paper delivers practical knowledge alongside best practices to help organizations adopt IoT systems which create adaptable efficient deliver chains with sustainability at their core thus achieving long-term market benefits in today's complex global marketplace. © 2025 IEEE.

关键词： Inventory control

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 << < 82 83 84 85 86 87 88 89 90 91 > >>

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：