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

68,197 篇 会议
417 篇 期刊文献
209 册 图书

馆藏范围

68,823 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

39,463 篇 工学
- 31,408 篇 计算机科学与技术...
- 26,745 篇 软件工程
- 11,897 篇 信息与通信工程
- 9,703 篇 控制科学与工程
- 7,425 篇 生物工程
- 6,372 篇 电气工程
- 4,617 篇 生物医学工程（可授...
- 3,989 篇 电子科学与技术（可...
- 3,670 篇 机械工程
- 3,648 篇 光学工程
- 3,233 篇 动力工程及工程热...
- 3,129 篇 网络空间安全
- 2,674 篇 安全科学与工程
- 2,666 篇 交通运输工程
- 2,282 篇 化学工程与技术
- 2,087 篇 仪器科学与技术
21,535 篇 理学
- 10,279 篇 数学
- 7,809 篇 生物学
- 5,419 篇 物理学
- 3,636 篇 统计学（可授理学、...
- 2,667 篇 化学
- 2,025 篇 系统科学
12,208 篇 管理学
- 7,052 篇 管理科学与工程(可...
- 5,980 篇 图书情报与档案管...
- 3,692 篇 工商管理
4,427 篇 医学
- 3,725 篇 临床医学
- 3,624 篇 基础医学(可授医学...
- 2,538 篇 药学(可授医学、理...
- 2,032 篇 公共卫生与预防医...
2,812 篇 法学
- 2,255 篇 社会学
1,641 篇 经济学
1,371 篇 农学
1,143 篇 教育学
405 篇 文学
149 篇 军事学
12 篇 艺术学
6 篇 哲学
2 篇 历史学

主题

1,732 篇 deep learning
1,298 篇 machine learning
1,021 篇 internet of thin...
698 篇 support vector m...
686 篇 feature extracti...
677 篇 blockchain
673 篇 computer vision
659 篇 object detection
567 篇 convolutional ne...
524 篇 forecasting
483 篇 training
437 篇 computational mo...
403 篇 artificial intel...
401 篇 covid-19
386 篇 reinforcement le...
339 篇 long short-term ...
325 篇 predictive model...
311 篇 automation
283 篇 image segmentati...
282 篇 big data

机构

506 篇 chitkara univers...
242 篇 school of comput...
201 篇 university of sc...
184 篇 school of automa...
166 篇 computer science...
142 篇 maharishi school...
129 篇 the islamic univ...
115 篇 computer science...
99 篇 karnataka bangal...
95 篇 school of comput...
89 篇 university of el...
86 篇 huazhong univers...
82 篇 college of compu...
82 篇 department of co...
82 篇 university of ch...
78 篇 school of comput...
78 篇 institute of art...
76 篇 school of comput...
76 篇 medical technica...
74 篇 computer technol...

作者

64 篇 shiva mehta
58 篇 vinay kukreja
54 篇 li yang
48 篇 kukreja vinay
45 篇 sharma vikrant
44 篇 sharma neha
42 篇 deepak gerard
41 篇 calvo d.
41 篇 wang lei
40 篇 wang jing
39 篇 ferrara g.
39 篇 ardid m.
39 篇 gagliardini s.
39 篇 li peng
39 篇 zhang lei
39 篇 rakesh kumar
36 篇 zhang tao
35 篇 chen a.
35 篇 benoit d.m.
35 篇 eddymaoui a.

语言

66,238 篇 英文
2,561 篇 其他
588 篇 中文
1 篇 西班牙文

检索条件"任意字段=2023 International Conference on Computer Science and Automation Technology, CSAT 2023"

共 68823 条记录，以下是921-930 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：

Data-Driven Robust Designs of Performance Prediction and Its Application in High-speed Trains 8

Data-Driven Robust Designs of Performance Prediction and Its...

引用

8th IEEE international conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Chen, Hongtian Wang, Weijun Guo, Dongsheng Xu, Shuiqing Cheng, Chao Shanghai Jiao Tong University Department of Automation Shanghai200240 China School of Mathematics and Statistics Changchun University of Technology Changchun130000 China School of Information and Communication Engineering Hainan University Haikou570228 China School of Electrical Engineering and Automation Hefei University of Technology Hefei230009 China School of Computer Science and Engineering Changchun University of Technology Changchun130000 China

ISBN: (纸本)9798350300178

This paper presents a robust performance prediction scheme for traction systems in high-speed trains. Performance variables are latent indicators of the system running, which play an important role in automated monitoring and fault diagnosis. It can be inferred from manifest variables (measurements) instead of directly observed from traction systems. Recently, most studies explored the static method for predictions, which is not suitable for dynamic systems. Considering the tricky challenges in practice, the existing prediction methods need to be further improved. Motivated by this, the paper designs a data-driven prediction model for performance variables of traction systems in high-speed trains. Specifically, to remove the influence of disturbances or noises, a robust subspace identification skill is adopted, which is developed for the soft sensor. In addition, this study further reduces the process errors of estimations in the state-space model. This method is verified on a traction system platform and an actual traction motor experiment. The experimental results prove the effectiveness and superiority of the proposed scheme. © 2023 IEEE.

关键词： Vehicle performance

来源：评论

学校读者我要写书评

暂无评论

Research on Sage- Husa Based Positioning Method for Maglev Trains 6

Research on Sage- Husa Based Positioning Method for Maglev T...

引用

6th international conference on Electronics and Communication, Network and computer technology, ECNCT 2024

作者： Hu, Qian Fan, Kuangang Cai, Wenlong School of Electrical Engineering and Automation Jiangxi University of Science and Technology Ganzhou China

ISBN: (纸本)9798350366143

The positioning of the maglev trains is closely related to the weight distribution of observations and noise estimation, for the traditional weighting and environmental noise interference and other problems, this paper adopts the weight distribution method to optimize the conventional weighting, uses Sage- Husa for noise estimation, and combines Kalman filtering to form AKF finally. Through the filtering results and error evaluation indexes, it can be obtained that the results of AKF filtering are closer to the real value, and its error is smaller. The mistake of AKF is smaller. This shows that the proposed method has some advantages in terms of accuracy for train positioning. © 2024 IEEE.

关键词： Information fusion

来源：评论

学校读者我要写书评

暂无评论

Insomnia Detection using Machine Learning Classifiers

Insomnia Detection using Machine Learning Classifiers

引用

2023 international conference on New Frontiers in Communication, automation, Management and Security, ICCAMS 2023

作者： Arya, Ashima Kaur, Ramneet Goyal, Deepam Gupta, Deepali Shilpa Juneja, Sapna Kiet Group of Institutions Delhi Ncr Ghaziabad India Sharda University Department of Computer Science & Engineering Greater Noida India Chitkara University Institute of Engineering & Technology Chitkara University Punjab India Chandigarh University Mohali India

ISBN: (纸本)9798350317060

The inability to fall asleep, stay asleep, or have non-restorative sleep is known as insomnia. This disorder can significantly lower an individual's quality of life in most poor nations. The study aimed to assess this methodology's efficacy and identify risk factors linked to sleep problems using machine learning techniques. By analyzing a large dataset and employing advanced algorithms, the researchers sought to uncover significant predictors of sleep disabilities and understand the performance of machine learning in this context. In this paper, analysis is done by random forest and LGBM classifiers. The dataset consist of 99,997 participants and their age is between 35-65 years. The comprehensive analysis is also performed and the dataset is fetched from Scopus database. © 2023 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

SS-DBSCAN: Epsilon Estimation with Stratified Sampling for Density-Based Spatial Clustering of Applications with Noise

SS-DBSCAN: Epsilon Estimation with Stratified Sampling for D...

引用

2023 international conference on automation, Control and Electronics Engineering, CACEE 2023

作者： Monko, Gloriana Joseph Kimura, Masaomi Shibaura Institute of Technology Graduate School Department of Functional Control Systems Tokyo Japan Shibaura Institute of Technology Department of Computer Science and Engineering Tokyo Japan

ISBN: (纸本)9798350309201

Clustering algorithms are crucial in uncovering hidden patterns and structures within datasets. Among the density-based clustering algorithms, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) has gained considerable attention for its effectiveness in various applications. However, determining appropriate parameter values for this algorithm remains a challenging task. This paper presents a novel methodology for eps parameter estimation for an improved DBSCAN, namely SS-DBSCAN. The experimental results across nine datasets demonstrate the efficacy of our proposed method in accurately determining clusters with eps value from SS-DBSCAN algorithm. The clusters identified using estimated eps values by SS-DBSCAN align well with the inherent structure of the datasets, yielding better cluster results than the manually set parameters and other methods used for automatic estimations of the eps for DBSCAN. Our approach adapted well to the peculiarities of each dataset, whether dealing with different scales, dimensions, or densities;it proved the versatility and robustness across various datasets, thereby emphasizing its generalizability and potential for broader applications. © 2023 IEEE.

关键词： Parameter estimation

来源：评论

学校读者我要写书评

暂无评论

Identification of Switched Gated Recurrent Neural Networks Using the EM Algorithm 5

Identification of Switched Gated Recurrent Neural Networks U...

引用

5th international conference on Data-Driven Optimization of Complex Systems, DOCS 2023

作者： Bai, Wentao Gu, Suhang Yan, Chao Zhang, Haoyu Jiang, Chunli Guo, Fan School of Computer Science and Engineering Changshu Institute of Technology Changshu China School of Electrical Engineering and Automation Changshu Institute of Technology Changshu China School of Information Science and Technology Hangzhou Normal University Hangzhou China School of Software Engineering Chongqing University of Posts and Telecommunications Chongqing China School of Automation Nanjing Institute of Technology Nanjing China

ISBN: (纸本)9798350393521

In the domain of nonlinear hybrid dynamic system modeling, the effectiveness of switched autoregressive exogenous (SARX) systems may face certain restrictions. To address this issue, this paper presents an enhanced switched system framework. In this framework, all SARX subsystems are replaced with gated recurrent neural networks, aiming to overcome these limitations. Importantly, the proposed switched system does not rely on any prior assumptions about the knowledge of operating modes. Finally, a new identification method is proposed based on the expectation-maximization (EM) algorithm, and its effectiveness is validated through a simulation example. © 2023 IEEE.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

On Identifying Communities in Online Hate Speech

On Identifying Communities in Online Hate Speech

引用

2023 international conference on New Frontiers in Communication, automation, Management and Security, ICCAMS 2023

作者： Burman, Ayusha Karan, Shaswata Mallik, Shreya Majee, Drishti Bal, Mayukh Anand, Sumit Chakraborty, Amartya University of Engineering & Management Department of Computer Science and Engineering Kolkata India St. Thomas' College of Engineering and Technology Department of Computer Science and Engineering Kolkata India

ISBN: (纸本)9798350317060

Hate Speech is one of the most dangerous problems which disturbs social and religious harmony. Social media which plays a vital role in our lives has now become a responsible element in spreading hate speech. This work presents a comprehensive analysis of hate speech on Twitter, using Tweepy, an open-source Twitter API, to fetch relevant data. Our study sought to investigate the behavioral patterns of users responsible for spreading hateful comments online. After collecting a sample of tweets, standard sentiment analysis techniques have been leveraged to segregate the tweets as per their positive and negative sentiments. Using Affin lexicon and TextBlob libraries, the polarity and subjectivity of the tweets have been identified. The k-means clustering algorithm is utilized to group the data into positive and negative clusters. These clusters have been considered as communities of the users and further analyzed. Standard metrics indicate a strong community formation in our proposed approach. The feasibility of clustering the features of user expressions toward community formation in social networks is explored in this work. Our findings provide valuable insights into the prevalence and nature of hate speech on social media and offer suggestions for addressing this critical issue. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Research on Virtual Training System of Robot-assisted Surgery based on Unity3D 20

Research on Virtual Training System of Robot-assisted Surger...

引用

20th IEEE international conference on Mechatronics and automation, ICMA 2023

作者： Zhu, Ling Cao, Guoxian Guo, Yuan Qiqihar University School of Mechanical and Electronic Engineering Heilongjiang Province Qiqihar China Harbin University of Science and Technology School of Computer Science and Technology Heilongjiang Province Harbin China

ISBN: (纸本)9798350320831

Aiming at the background of robot-assisted minimally invasive surgery, a virtual training system was built based on Unity3D platform for training surgeons to operate surgical robots. The training scene was optimized by texture mapping, lighting adjustment and rendering plug-in, and the UI interface of the system was designed. The mapping relationship between the force feedback device and the virtual surgical instrument was established to realize the control of the opening and closing, pitching, rotation and movement around the constrained position of the virtual surgical instrument. The classification idea of different virtual objects using different collision components was proposed, and the collision frame of surgical instruments was refined to realize the accurate simulation of colliding, clamping, moving, throwing, and hooking. The feedback force data showed the stability of the system during the simulation of different interactive training. © 2023 IEEE.

关键词： Robotic surgery

来源：评论

学校读者我要写书评

暂无评论

Application of computer 3D Image Vision technology in Intelligent Retrieval System 3

Application of Computer 3D Image Vision Technology in Intell...

引用

2023 IEEE 3rd international conference on Data science and computer Application, ICDSCA 2023

作者： Siqi, Song Shanghai University School of Management Shanghai China

ISBN: (纸本)9798350341546

This article introduces the shortcomings of the current search engine. A personalized information retrieval system model based on 3D image vision technology is presented. This paper proposes a personalized information search architecture based on intelligent agent. The method uses the upper computer to calculate and operate, the bottom computer to interact with the user and display the query results. The general framework of the software and the concrete implementation scheme of each function module are given. In this method, a semantically based association model is constructed using the existing markup data, and it is integrated with the visual characteristics of the image. Thus, the correlation feedback is efficiently completed on two levels. The experimental results show that the method is fast, accurate and reliable. © 2023 IEEE.

关键词： 3D images gray co-occurrence matrix intelligent retrieval system Visual technology

来源：评论

学校读者我要写书评

暂无评论

A Review of the Development of Vision Transformer

A Review of the Development of Vision Transformer

引用

2023 international conference on Artificial Intelligence and automation Control, AIAC 2023

作者： Bao, Suyan Ding, Hui Chen, Hang Beijing Aerospace Wanyuan Science & Technology Co. Ltd Beijing100176 China Beijing Jiaotong University Beijing100091 China

ISBN: (纸本)9798350383805

Transformer is an encoder-decoder model based on self-attention mechanism. It was initially applied in the field of natural language processing due to its novel architecture design and remarkable performance. With the continuous development of transformer models in recent years, many researchers have been studying how to apply this model to computer vision and have produced many innovative results. The most representative ones are image classification, object detection, and image segmentation. Currently, vision transformers are still a hot research topic, and transformer-based visual technologies are widely used in fields such as medicine and education. This article starts from the basics of the transformer model, summarizes its recent development achievements and applications, and elaborates on the structure and principles of the Vision Transformer model. It also introduces recent development achievements of visual transformers in model architecture, parameters and computational efficiency. Finally, the article summarizes the problems and difficulties existing in various models of vision transformers and points out the future development direction. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Crime Scene Prediction for Unmanned Aerial Vehicles Investigation via Machine Learning 8

Crime Scene Prediction for Unmanned Aerial Vehicles Investig...

引用

8th international conference on automation, Control and Robotics Engineering, CACRE 2023

作者： Ojo, Taiwo P. Chi, Hongmei Hilliard, Emmanuel Yan, Jie Florida AandM University Dept. of Computer and Info Science TallahasseeFL32307 United States Bowie State University Dept. of Computer Science BowieMD20715-9465 United States

ISBN: (纸本)9798350302776

Unmanned Aerial Vehicles have increased their applicability in evidence gathering for collecting digital evidence. Authenticating this evidence depends on the crime scenario and the type of drones used. With drones, the evidence type could be the GPS location, the communication signal, the flight log, and the multimedia evidence. These are forms of evidence that forensic experts use to finalize crime cases. Analyzing this evidence requires expensive forensic toolsets. This paper will investigate the level of accuracy and performance verification of machine learning algorithms such as Convolutional Neural Networks (CNN), Support Vector Machines (SVM), and Long Short-Term Memory (LSTM) can reach in identifying vehicle information and the details of the people inside the vehicle at the crime scene and starting with the level of identifying the minute details for the investigation. The performance of the machine learning algorithms will analyze the evidence for deepfakes and possible manipulations in the evidence gathered. © 2023 IEEE.

关键词： Support vector machines

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 << < 89 90 91 92 93 94 95 96 97 98 > >>

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：