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

45,923 篇 会议
1,014 册 图书
654 篇 期刊文献
2 篇 学位论文

馆藏范围

47,592 篇 电子文献
8 种 纸本馆藏

日期分布

学科分类号

30,788 篇 工学
- 16,931 篇 计算机科学与技术...
- 14,104 篇 软件工程
- 8,186 篇 控制科学与工程
- 5,512 篇 机械工程
- 5,232 篇 信息与通信工程
- 3,651 篇 电气工程
- 3,339 篇 化学工程与技术
- 3,244 篇 生物工程
- 2,902 篇 生物医学工程（可授...
- 2,687 篇 电子科学与技术（可...
- 2,652 篇 材料科学与工程（可...
- 2,535 篇 仪器科学与技术
- 2,385 篇 动力工程及工程热...
- 2,050 篇 光学工程
- 2,044 篇 力学（可授工学、理...
- 1,923 篇 土木工程
- 1,593 篇 建筑学
- 1,409 篇 冶金工程
- 1,387 篇 交通运输工程
15,497 篇 理学
- 6,821 篇 数学
- 4,997 篇 物理学
- 3,562 篇 生物学
- 2,746 篇 化学
- 2,007 篇 统计学（可授理学、...
- 1,531 篇 系统科学
6,972 篇 管理学
- 4,608 篇 管理科学与工程(可...
- 2,517 篇 图书情报与档案管...
- 2,396 篇 工商管理
2,409 篇 医学
- 2,086 篇 临床医学
- 1,850 篇 基础医学(可授医学...
1,197 篇 法学
1,183 篇 经济学
885 篇 教育学
885 篇 农学
177 篇 军事学
162 篇 文学
53 篇 艺术学
12 篇 哲学
2 篇 历史学

主题

1,163 篇 accuracy
1,135 篇 robots
901 篇 robot sensing sy...
862 篇 feature extracti...
799 篇 deep learning
773 篇 training
720 篇 real-time system...
650 篇 artificial intel...
641 篇 mobile robots
615 篇 computational mo...
507 篇 machine learning
478 篇 support vector m...
463 篇 internet of thin...
456 篇 convolutional ne...
448 篇 visualization
427 篇 robot kinematics
403 篇 robotics and aut...
391 篇 predictive model...
388 篇 robustness
376 篇 control systems

机构

128 篇 department of co...
74 篇 school of mechan...
68 篇 maharishi school...
67 篇 university of sc...
64 篇 school of automa...
63 篇 department of co...
54 篇 school of automa...
53 篇 chitkara univers...
53 篇 university of ch...
50 篇 college of infor...
45 篇 school of mechan...
42 篇 department of el...
40 篇 school of comput...
39 篇 school of mechan...
38 篇 computer science...
35 篇 department of el...
35 篇 vishwakarma inst...
35 篇 maharishi univer...
35 篇 faculty of infor...
34 篇 state key labora...

作者

40 篇 wang lei
39 篇 zhang lei
38 篇 liu yang
33 篇 youngil youm
31 篇 wu xinyu
27 篇 zhang tao
27 篇 li xin
25 篇 lei wang
25 篇 munsang kim
25 篇 sharma vishnu
24 篇 zexiang li
23 篇 li yang
23 篇 wang jian
22 篇 xinyu wu
22 篇 li peng
22 篇 rakesh kumar
22 篇 wang jing
22 篇 li yibin
21 篇 wang hui
20 篇 qingsong xu

语言

46,010 篇 英文
1,214 篇 其他
426 篇 中文
1 篇 法文
1 篇 朝鲜文

检索条件"任意字段=International Conference on Advances in Science, Engineering and Robotics Technology"

共 47594 条记录，以下是4931-4940 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：

RDDS: Road Disease Detection Model Based on YOLOv5 14

RDDS: Road Disease Detection Model Based on YOLOv5

引用

14th IEEE international conference on Cyber technology in Automation, Control, and Intelligent Systems, CYBER 2024

作者： Han, Zhiqiang Gong, Jun Qiao, Yu School of Vehicle and Transportation Engineering Taiyuan University of Science and Technology Taiyuan030024 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China

ISBN: (纸本)9798331506056

The utilization of intelligent vehicles for detecting road anomalies has become a relatively common phenomenon. The existing road disease detection workload is large, the robustness is not high, and small diseases are easily ignored, which brings huge challenges to road disease detection. A road disease detection model named RDDS based on YOLOv5 is proposed. Based on the YOLOv5 algorithm, we incorporate Transformer encoder blocks into the head part to form Transformer Prediction Heads (TFE), expanding their number to four. This enhancement aims to improve the model's capability to detect small targets and road diseases of different scales. In addition, we introduce the convolutional block attention model (CBAM) to make the network pay more attention to important channels and spatial locations, thereby improving the performance and generalization ability of the model. Aiming at the problems of low resolution and insufficient data volume in current road disease data sets, we propose a new road disease detection data set RDDSC. Finally, we conducted experiments on the RDDSC data set. The experimental results showed that compared with the original YOLOv5, the RDDS parameters increased slightly, while the detection accuracy was significantly improved. Compared with existing detection algorithms, RDDS has obvious advantages in road disease detection. © 2024 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Roles of IoT in Business and Marketing Areas Challenges and Prediction 14

Roles of IoT in Business and Marketing Areas Challenges and ...

引用

14th international conference on advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Vinta, Surendra Reddy Praveena, B.V.N. Vivekanandhan, V. Dhanalaxmi, B. School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravathi India Dept of CSE DVR and Dr.HS MIC College of Technology Andhra Pradesh Kanchikacherka India Telangana Hyderabad500100 India

This paper explores IoT applications in marketing research and provides information on how organizations are using IoT devices and other emerging technologies such as artificial intelligence (AI), machines learning (ML), and social networks to promote various products and services. Moreover, this study shows how the consistent use of IoT technologies leads to significant organizational competitiveness. Paper too explains how IoT can be called a new component of business intelligence and digital marketing discusses the challenges associated with implementing IoT solutions. The Internet of Things (IoT) is now evolving into a global infrastructure that provides complex services connection of different things (physical and virtual) based on information system technology. This research shows the role of Internet of Things (IoT) technology in business and marketing. In particular, this study is also deeply revealing IoT technology to understand the various key elements, operational domains and their various use cases technology in business and marketing. © Grenze Scientific Society, 2023.

关键词： Marketing

来源：评论

学校读者我要写书评

暂无评论

Virtual Keyboard System Based on IMU Glove 2

Virtual Keyboard System Based on IMU Glove

引用

2nd international conference on Artificial Intelligence, Human-Computer Interaction and robotics, AIHCIR 2023

作者： Wang, Xinyi Meng, Jin Zhang, Haoyang Yan, Ye Xie, Liang Yin, Erwei School of Information Science and Engineering East China University of Science and Technology Shanghai China Defense Innovation Institute Academy of Military Sciences Beijing China

ISBN: (纸本)9798350360363

Portable text entry systems on mobile computing devices have been increasingly demanded to facilitate daily use. Unfortunately, existing virtual keyboards struggle to trade off text input accuracy and user-friendliness well. Thus, inspired by the well-accepted and oft-used QWERTY layout, a novel IMU-based virtual keyboard system is proposed to achieve efficient and user-friendly text input. In this system, an exquisite data glove integrated with six IMU sensors is designed to capture hand motion signals during keystrokes. With the aim of predicting the corresponding typing outputs, a hand gesture decoding algorithm called VK-GR is proposed, which can effectively handle noise interference and extract spatial details as well as sequential features. To support the training and validation of the algorithm, a keystroke gesture dataset from 13 individuals is collected. Experiments show that the proposed system enables users to type on mobile devices with limited learning costs, achieving an offline accuracy of 95.61% and an online accuracy of 78.3%, along with a real-time input speed of 29.99 WPM. © 2023 IEEE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Applying Cost-Sensitive Learning Methods to Improve Extremely Unbalanced Big Data Problems Using Random Forest 2

Applying Cost-Sensitive Learning Methods to Improve Extremel...

引用

2nd IEEE international conference on advances in Computing, Communication and Applied Informatics, ACCAI 2023

作者： Ramana, K. Venkata Yuvasri, B. Sultanuddin, S.J. Ponsudha, P. Sowmya, P.D. Sangeetha, A. Visva Engineering and Technology Department of Computer Science and Engineering Telangana Hyderabad500 090 India Rmk College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Puduvayal601206 India Kl Deemed to Be University Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram522302 India Velammal Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai600053 India Reva University Department of Csa Karnataka Bengaluru560064 India Department of English Tamil Nadu Dindigul624622 India

ISBN: (纸本)9798350315905

In a larger part minority characterization issue, class irregularity in the dataset(s) can definitely misshape the exhibition of classifiers, creating an expectation predisposition for the greater part class. A negative (larger part) class expectation predisposition could make impeding impacts if the positive (minority) class is the gathering of interest and the application region being referred to states that a false negative is significantly more costly than a false certain. The decrease of class divergence is made more troublesome by big data because of the different and muddled design of the similarly bigger datasets. This exploration presents a wide evaluation of distributed works inside the past 8 years, zeroed in on fashionable unevenness (i.e., a greater part to-minority class proportion somewhere in the range of 100:1 and 10,000:1) in big data to survey the cutting edge in addressing ominous outcomes connected with class irregularity. In this paper we propose two methods for managing the imbalanced data grouping issue utilizing irregular backwoods. The other depends on an inspecting approach, though the first depends on cost-sensitive learning. Execution pointers like review and exactness, false-positive and false-negative rates. © 2023 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

An Integrative Machine Learning Strategy for the Prognosis of Heart Disease 1

引用

5th international conference on advances in Information Communication technology and Computing, AICTC 2024

作者： Hossain, Md. Ashraful Nuruzzaman Nobel, S.M. Mohsin Kabir, Md. Mridha, M.F. Shin, Jungpil Department of Computer Science and Engineering Bangladesh University of Business and Technology Dhaka1216 Bangladesh Superior Polytechnic School University of Girona Girona17071 Spain Department of Computer Science American International University-Bangladesh Dhaka1229 Bangladesh Department of Computer Science and Engineering University of Aizu Aizuwakamatsu Japan

ISBN: (数字)9789819761036

ISBN: (纸本)9789819761029

The incidence of heart disease is concerning, and timely detection is essential for improving the health of patients. Machine learning has shown potential in assisting in the prognosis of heart conditions. This research evaluated the effectiveness of various machine learning algorithms, including Random Forest, XGBoost, LGBM, and CatBoost, in accurately predicting instances of heart disease. Furthermore, we suggested a hybrid model that integrates all four models, yielding a 97.50% accuracy rate, 0.98% precision value, 0.97% recall value, and 0.98% F1-score. This hybrid model surpasses both individual models and current methodologies. The study utilized the "Heart Failure Prediction Dataset" acquired from Kaggle, which consisted of 11 prevalent variables such as age, blood pressure, and cholesterol levels. These findings indicate that the hybrid model has promise as a powerful tool for predicting heart disease. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Design and Evaluation of a Robotic Drilling Screw End-Effector for Minimally Invasive Spine Surgery 11

Design and Evaluation of a Robotic Drilling Screw End-Effect...

引用

11th RSI international conference on robotics and Mechatronics, ICRoM 2023

作者： Talkhoncheh, Ali Bakhshian Beigzadeh, Borhan Iran University of Science and Technology Biomechatronics and Cognitive Engineering Research Lab School of Mechanical Engineering Tehran Iran

ISBN: (纸本)9798350308105

Spinal surgery is a common treatment for various spinal conditions, such as scoliosis, herniated discs, spinal stenosis, fractures, tumors, deformities, instability, and cord injuries. However, challenges in precise drilling and screw implantation have spurred interest in less invasive methods with reduced human involvement. Robotic spine surgery offers increased accuracy, efficiency, and the potential for remote surgeries during situations like the COVID-19 pandemic. This study presents the design and evaluation of a drilling screwing end-effector (DSEE) to minimize human intervention in spinal surgery. The DSEE incorporates a specialized DC motor and gearbox for seamless transition between drilling and screwing modes. A YZC-133 load cell measures reaction force during bone drilling. Performance evaluation was conducted through laboratory and in vitro tests. A complete factorial design using a fresh calf femur bone specimen investigated influential parameters in bone drilling. Results highlight the significant impact of drill-bit diameter, feed rate, and drill spindle speed, consistent with previous research. In summary, this research contributes to spinal surgery by developing and evaluating a robotic drilling screw end-effector. By enhancing precision and reducing human involvement, this technology shows promise for diverse spinal conditions. Findings illuminate influential factors in bone drilling force, advancing minimally invasive surgical techniques for varied spinal pathologies. © 2023 IEEE.

关键词： Screws

来源：评论

学校读者我要写书评

暂无评论

Predictive Correlation Frameworks for Optimized CPU Sensing and System Call Coordination 2

Predictive Correlation Frameworks for Optimized CPU Sensing ...

引用

2nd IEEE international conference on Recent advances in Information technology for Sustainable Development, ICRAIS 2024

作者： Sheeba Rani, S. Vijaya, P. Maheswari, R. Sree Vishnu Varthini, S. Sri Eshwar College of Engineering Electronics and Communication Engineering Department Coimbatore India Modern College of Business and Science Department of Mathematics and Computer Science Bowshar Oman Rajalakshmi Institute of Technology Dean Innovations Chennai India

ISBN: (纸本)9798350354461

The computing system has a complex topography that greatly affects CPU execution time due to the dynamic interplay between program execution and system resource allocation, which is mediated by several Operating System (OS) calls. The system uses a clever hybrid predictive model that smoothly combines the potent LightGBM and CatBoost algorithms to uncover this complex link. Through careful data collecting, processing, and model training, this research aims to fully comprehend and quantify the effect of system calls on CPU execution time. The analysis is based on running various programs under the vigilant eye of Strace, a potent system call tracking utility. 377 Python code samples were carefully selected from different GitHub repositories to ensure a representative and varied range of settings for the study. It creates a solid dataset that forms the basis of the analytical efforts by gathering comprehensive information on system calls and the accompanying CPU execution durations. A key part of the procedure is the data pretreatment stage, which involves using sophisticated data conversion algorithms and regular expressions (regex) sparingly. The result of this painstaking formatting and cleaning procedure is a well-organized and polished CSV file that it uses as the input for the predictive model. This procedure guarantees the removal of noise and improves the model's capacity to identify significant patterns in the data. The next stage of the study is to use the well-selected and prepared dataset to train the hybrid prediction model. By combining the advantages of LightGBM and CatBoost algorithms, it can take full advantage of their own strengths and use their special powers to extract complex associations from the data. In order to find the hidden relationships between system calls and CPU execution time, this training procedure is essential. The main goal is to navigate the terrain of the results is to offer a numerical evaluation of the relationship between sys

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

An Efficient Smart-IoT-Aided Waste Management System with Optimal Shortest Path Routing Using Mud Ring Algorithm 3

An Efficient Smart-IoT-Aided Waste Management System with Op...

引用

3rd IEEE international conference on Recent advances in Systems science and engineering, RASSE 2023

作者： Satyanarayana Kona, V.V. Subramoniam, M. Binson, V.A. Sathyabama Institute of Science and Technology Faculty of Electronic Engineering Tamil Nadu India Sathyabama Institute of Science and Technology Faculty of Electrical and Electronics Engineering Tamil Nadu India Saintgits College of Engineering Department of ECE Kerala Kottayam India

ISBN: (纸本)9798350341676

The waste management is a problem for the modern cities as it affects the sustainability of the environment and on the stage of standard recognized by the people. In the past few years, some changes have done in the path of presenting a door-To-door private garbage gathering. An important factor for the victory of these activities is to attain better cooperation from humans. The digital change operation in this field needs much time other than a better handling of information related to the garbage collection approaches. The conventional garbage maintenance model performs according to the daily schedule that is very costly and inefficient. The conventional recycle bin has also revealed its ineffectiveness because of the improper recycling of the waste by the people. With the improvement of 'Internet of Things (IoT) and Artificial Intelligence (AI)', the conventional garbage handling model can be exchanged with smart sensors enclosed into the device to process real-Time observation and permit for good garbage handling. Hence, to resolve the complication presented in the conventional waste management system, an innovative waste management framework is designed based on deep learning techniques. Initially, essential data for the analysis is occurred from benchmark resources and subjected to weight computing region. Here, the weights computation is performed based on trashcan type and capacity. Next, the weight computed data is utilized to identify the shortest path for the waste-collecting vehicle to reach the suitable waste centers. Moreover, the optimal paths are selected by utilizing Mud Ring Algorithm (MRA) optimization technique. Hence, the implemented waste management system secures a better performance rate than the conventional techniques in different experimental observations. © 2023 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Research on task scheduling and path planning in intelligent warehousing system 3

Research on task scheduling and path planning in intelligent...

引用

3rd international conference on Control and Intelligent robotics, ICCIR 2023

作者： Tian, Renhui Zhu, Linkai Cai, Zhiming City University of Macau Macau China Information Technology School Hebei University of Economics and Business Shijiazhuang China Macau Millennium College Macau China

ISBN: (纸本)9781510671867

Traditional warehouse logistics has faced huge challenges with the development of China’s information technology industry. Intelligent logistics, especially intelligent warehousing, has become a hot research topic worldwide. Amazon Kiva system, a representative of intelligent warehouse handling systems based on multiple mobile robots, has revolutionized the warehousing industry with its "goods-to-man" picking model, which reduces the time and labor costs of finding goods. However, this model still has many limitations, such as low efficiency and scalability, when dealing with large-scale picking tasks. In this paper, we propose a novel intelligent warehouse handling system that overcomes these limitations and improves the system performance. We present the system architecture, design principles, and key algorithms of our system, and evaluate its effectiveness and robustness through simulations and experiments. Specifically, we propose an order task scheduling algorithm based on order adaptation and discrete particle swarm optimization, and a path planning algorithm based on 2D planar graph for the warehouse scenario. We show that our integrated algorithm can improve the system efficiency by solving the two key problems of order scheduling and route planning in the smart storage system. © 2023 SPIE.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

An Innovative New Open Computer Vision Framework Via Artificial Intelligence with Python

An Innovative New Open Computer Vision Framework Via Artific...

引用

international conference on Data science and Network engineering, ICDSNE 2023

作者： Bonkra, Anupam Dhiman, Pummy Goyal, Shanky Islam, Sardar M. N. Rana, Arun Kumar Sharma, Naman Information Technology Department Chandigarh Engineering College-CGC Punjab India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India ISILC & Decision Sciences and Modelling Program Victoria University Footscra Australia Department of Computer Science Galgotias College of Engineering of Technology Uttar Pradesh Greater Noida India

ISBN: (纸本)9789819967544

Computer vision has emerged as an important subject of study, with several practical applications in a wide range of domains. OpenCV, a widely used framework, has played an important role in allowing computer vision tasks. This study presents an AI-driven Python implementation of the OpenCV framework to expand its capabilities. Data collecting and pre-processing, feature extraction, model selection and training, and Python-based system implementation are all part of the proposed system. A thorough examination of system performance indicates its advantage over competing approaches. The system’s flexibility enables it to handle a variety of computer vision tasks, such as gesture recognition, face detection, and object recognition. This paper advances AI-powered computer vision systems by providing significant insights into the implementation of OpenCV with Python. The focus of future work will be on improving system accuracy and broadening its functional range. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Python

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 << < 490 491 492 493 494 495 496 497 498 499 > >>

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：