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

890 篇 会议
5 篇 期刊文献
4 册 图书

馆藏范围

899 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

611 篇 工学
- 514 篇 计算机科学与技术...
- 320 篇 软件工程
- 102 篇 信息与通信工程
- 94 篇 电气工程
- 78 篇 生物工程
- 72 篇 控制科学与工程
- 47 篇 环境科学与工程（可...
- 35 篇 机械工程
- 35 篇 安全科学与工程
- 30 篇 交通运输工程
- 29 篇 生物医学工程（可授...
- 28 篇 动力工程及工程热...
- 24 篇 建筑学
- 23 篇 光学工程
- 18 篇 电子科学与技术（可...
186 篇 理学
- 87 篇 数学
- 81 篇 生物学
- 30 篇 统计学（可授理学、...
- 29 篇 物理学
- 22 篇 系统科学
132 篇 管理学
- 99 篇 管理科学与工程(可...
- 50 篇 图书情报与档案管...
- 48 篇 工商管理
112 篇 教育学
- 111 篇 教育学
49 篇 法学
- 40 篇 社会学
36 篇 医学
- 35 篇 临床医学
- 34 篇 基础医学(可授医学...
- 25 篇 公共卫生与预防医...
21 篇 经济学
- 21 篇 应用经济学
19 篇 农学
- 19 篇 作物学
6 篇 军事学
4 篇 文学

主题

81 篇 machine learning
60 篇 deep learning
43 篇 internet of thin...
39 篇 accuracy
38 篇 ecosystems
25 篇 predictive model...
23 篇 reinforcement le...
23 篇 convolutional ne...
22 篇 training
19 篇 real-time system...
19 篇 feature extracti...
19 篇 security
19 篇 artificial intel...
18 篇 big data
18 篇 technological in...
17 篇 computational mo...
17 篇 students
17 篇 machine learning...
16 篇 sustainable deve...
16 篇 e-learning

机构

11 篇 chitkara centre ...
9 篇 department of in...
8 篇 chitkara univers...
8 篇 aslerd rome
7 篇 chitkara univers...
6 篇 centre of resear...
5 篇 department of co...
4 篇 texas a&m univer...
4 篇 czech tech univ ...
4 篇 bina nusantara u...
4 篇 lloyd institute ...
4 篇 the islamic univ...
4 篇 univ politehn bu...
4 篇 acad romanian sc...
4 篇 lloyd law colleg...
4 篇 univ innsbruck i...
3 篇 yunnan key labor...
3 篇 kkr and ksr inst...
3 篇 vishwakarma inst...
3 篇 universidad tecn...

作者

7 篇 giovannella carl...
6 篇 urban josef
5 篇 dascalu mihai
4 篇 bakken jeffrey p...
4 篇 uskov vladimir l...
4 篇 rachakonda rama
3 篇 heinemann collee...
3 篇 maranan ramya
3 篇 p. william
3 篇 refaat shady s.
3 篇 kaliszyk cezary
3 篇 olsak miroslav
3 篇 setiawan karli e...
3 篇 santos fernando ...
3 篇 leoste janika
3 篇 trausan-matu ste...
2 篇 m. vigenesh
2 篇 zhao huijuan
2 篇 toma irina
2 篇 a l n rao

语言

852 篇 英文
45 篇 其他
5 篇 中文
1 篇 法文

检索条件"任意字段=4th International Conference on Smart Learning Ecosystems and Regional Development"

共 899 条记录，以下是91-100 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：

OCTm: Custom Deep learning Model for Diagnosing Retinal Diseases 4

OCTm: Custom Deep Learning Model for Diagnosing Retinal Dise...

引用

4th international conference of Science and Information Technology in smart Administration, ICSINTESA 2024

作者： Al-Amiry, Shibly Hameed Al-Juboori, Ali Mohsin University of Al-Qadisiyah Department of Computer Science Al-Qadisiyah Iraq

ISBN: (纸本)9798350376111

the retina is one of the most essential parts of the vision process and may be exposed to many diseases that require early diagnosis. In this paper, we applied several pre-processing steps and proposed a custom convolutional neural network (CNN) model called (OCTm), which consists of many layers and includes both types of convolutional layers (2-D convolutional and separable convolutional) and both types of pooling layers (max and average). Has been implemented for diagnosing retinal diseases, namely Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), and DRUSEN, in optical coherence tomography (OCT) images in the UCSD-v2 dataset. It showed a high accuracy and speed that was able to obtain an accuracy of up to 99.79%, 100% specificity, 99.79% precision, and 99.69% sensitivity. When comparing the accuracy of the proposed model, it exceeds the results of previous studies. the Duke dataset was also used to verify the generalizability of the model and achieved an accuracy of 99.69%, a specificity of 100%, a precision of 99.69%, and a sensitivity of 99.69%. these results confirm the reliability of the use of artificial intelligence in the medical field. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Enhancing Gameplay Experience through Reinforcement learning in Games 4

Enhancing Gameplay Experience Through Reinforcement Learning...

引用

4th IEEE international conference on smart Information Systems and Technologies, SIST 2024

作者： Zhasulanov, Dinmukhammed Marat, Bekarys Erkin, Kuanysh Omirgaliyev, Ruslan Kushekkaliyev, Alman Zhakiyev, Nurkhat Department of Computer Engineering Astana IT University Astana Kazakhstan Department of Physics West Kazakhstan University Uralsk Kazakhstan Department of Science and Innovations Astana IT University Astana Kazakhstan

ISBN: (纸本)9798350374865

It is important to improve the game development field since games have great influence on economics and society. One of the ways to enhance game experience is to replace non-playable characters (NPC) by machine learning (ML) agents. Artificial Intelligence (AI) trained by Reinforcement learning algorithms can adapt to the game environment and act based on users’ actions or changes in surroundings. this research project aims to test the idea of replacing the NPC by artificial intelligence agent trained by Reinforcement learning algorithms. the data for this project was collected by observation of experiments inside of the game created in Unity platform. Agent was trained in special toolkit for Unity platform called "Unity ML-Agents". the behavior of the agents was subjected to preparatory measures for replication, including preliminary data processing using behavior cloning methods. the selected algorithm of the Reinforcement learning was the Proximal Policy Optimization, which is based on balance between new actions and its rewards. the training progress of the agents was monitored utilizing TensorBoard, the default package within the Unity ML Agents toolkit. During the research initialization phase, there were set null hypothesis, which states that pre-scripted bots are better for games and alternative hypothesis, which states that AI can replace NPC and enhance the game experience for a player. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Research on the learning Evaluation System of Vocational Education Driven by Big Data 4

Research on the Learning Evaluation System of Vocational Edu...

引用

4th international conference on Information Science and Education, ICISE-IE 2023

作者： Gao, Xun School of Accounting and Finance Wuxi Vocational Institute of Commerce Wuxi China

ISBN: (纸本)9798350394610

Benefiting from Education Informatization 2.0, the field of vocational education has generated a large amount of data, which has changed the way of 'teaching' and 'learning'. Today, the entire learning process can be identified and recorded. In order to solve the problems existing in the current digital teaching platform of vocational colleges, this study started from the three dimensions of learning attitude, learning process and learning effect, tracked students' learning situation, and constructed a teaching evaluation system. Use learning big data to diagnose problems, carry out teaching intervention, provide precise and personalized educational support, highlight the characteristics of learning management in the big data era, and promote the development of smart vocational education learning. © 2023 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Leveraging Machine learning Approach for Large-Scale Unstructured Satellite Image Analysis: A Comprehensive Review and Future Predictions 4

Leveraging Machine Learning Approach for Large-Scale Unstruc...

引用

4th IEEE international conference on smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2023

作者： Devendrakumar, S.M. Devanathan, M. Seeba Sri, R. Reva University India Panimalar Engineering College India

ISBN: (数字)9798350384628

ISBN: (纸本)9798350384628

In the last century, research on antennas and propagation (A&P) has progressed, influencing both technology and society. Even with a well-established theory of electromagnetics, ongoing A&P exploration is essential, particularly in the context of the Fourth Industrial Revolution. this paper employs natural language processing (NLP) and machine learning (ML) to connect historical and contemporary events. 2,415 keywords indicating important A&P themes were extracted from a systematic review of 160,000 papers published between 1981 and 2022. Using an encoder-decoder LSTM network similar to Gartner hype cycle, we predict future trends, offering important insights into the development of this important subject. © 2023 IEEE.

关键词： learning algorithms

来源：评论

学校读者我要写书评

暂无评论

AI in smart Manufacturing: An Ethical and Legal Perspective 4

AI in Smart Manufacturing: An Ethical and Legal Perspective

引用

4th international Multidisciplinary Information Technology and Engineering conference, IMITEC 2024

作者： Onu, Peter Pradhan, Anup Madonsela, Nelson Sizwe Bowen University Mechatronics Engineering Programme Iwo Nigeria University of Johannesburg Quality and Operaions Managment Johannesburg South Africa

ISBN: (纸本)9798350387988

the rapid advancement and deployment of Artificial Intelligence (AI) technologies in the manufacturing sector and the integration of the Internet of things (IoT) and big data analytics are transforming traditional manufacturing processes. this is significant for smart Manufacturing and poses immense potential for creating highly efficient, flexible, and interconnected production systems. However, these technological advancements come with substantial ethical and legal considerations that necessitate careful examination and proactive management. Using a qualitative research approach, this paper analyzes the ethical implications of AI implementation in manufacturing, exploring key challenges and opportunities for promoting responsible AI development. the paper presents a comprehensive review of emerging engineering solutions to address ethical concerns and protect intellectual property in the context of AI-driven smart Manufacturing. It discusses the potential of blockchain technology in ensuring data integrity and transparency, federated learning approaches for collaborative model training while preserving data privacy, and AI transparency mechanisms to enhance trust and accountability in AI systems. Based on previous cases, industry methods, and scholarly discussions, this study provides practical suggestions for dealing with the ethical and intellectual property challenges of integrating AI into manufacturing processes. © 2024 IEEE.

关键词： smart manufacturing

来源：评论

学校读者我要写书评

暂无评论

LabVIEW Integrated with Python Machine learning for DC Motor Drive 4

LabVIEW Integrated with Python Machine Learning for DC Motor...

引用

4th international conference of Science and Information Technology in smart Administration, ICSINTESA 2024

作者： Poyai, Mana Maneetham, Dechrit Sutyasadi, Petrus Rajamangala University of Technology Thanyaburi Faculty of Technical Education Department of Mechatronics Engineering Pathumthani Thailand Vocational Faculty Sanata Dharma University Department of Mechatronics Yogyakarta Indonesia

ISBN: (纸本)9798350376111

this study presents a new technique that integrates LabVIEW and Python to enhance the control of DC motor drives through the utilization of machine learning methods. the objective of our research is to leverage LabVIEW's graphical programming interface in combination with the Scikit-learn Python package to train a Polynomial Regression model. the goal is to forecast Pulse Width Modulation (PWM) values at desired Rotations per Minute (RPM) of a DC motor. the accuracy and reliability of the trained model are evaluated using performance assessment metrics such as the R-squared (R2) coefficient of determination and the Root Mean Square Error (RMSE). the R2 score assesses the precision of the model's fit, whereas the RMSE quantifies the model's predictive capability by comparing observed and predicted data. this research also includes a comparison between the machine learning technique for DC motor drive and conventional PID control. the findings illustrate the successful integration of LabVIEW and Python in managing DC motor drives, achieving low overshooting and faster attainment of the set RPM point compared to classical PID control. this emphasizes machine learning's capacity to enhance control strategies;the application of Polynomial Regression yields promising results, demonstrating its effectiveness in predicting PWM and RPM values with an R2 value ranging from 96% to 98% and RMSE within 19. © 2024 IEEE.

关键词： Python

来源：评论

学校读者我要写书评

暂无评论

Long Short-Term Memory Utilization for Non-Invertible Transformation Face Biometric Recognition System 4

Long Short-Term Memory Utilization for Non-Invertible Transf...

引用

4th international conference of Science and Information Technology in smart Administration, ICSINTESA 2024

作者： Alwan, Hiba Basim University of Technology - Iraq Department of Computer Science Baghdad Iraq

ISBN: (纸本)9798350376111

A recognition system is important in artificial intelligence research areas. It is broadly used for identification reasons and in several ways like facial recognition. Recognition systems depend on classification systems to work. Classification is a supervised learning technique. Long short-term memory is a type of supervised learning technique and can be used for classification purposes. Feature selection techniques have been used to improve the classification performance and reduce the training time. the black widow optimization algorithm is considered a kind of feature selection technique. Biometric systems are a particular type of recognition system. It influences the recognition system to accomplish its kernel work in identifying users based on the user's unique biometric data. Face images are broadly used as a biometric trait. Facial recognition is popular, because of its non-intrusive, technological development, and cameras, nowadays, everywhere. Facial recognition is a common selection for detecting known users in secret zones. In this paper, the black widow optimization algorithm has been used to select the suitable feature. then, the proposed non-invertible transformation method is performed to secure the selected feature. Finally, long short-term memory has been used as a classifier to classify known and unknown users. Two common datasets have been used to evaluate the proposed system. these datasets are FEI and Georgia Tech datasets. Two common measurements have been used to assess the proposed system. these measurements are the classification accuracy and the equal error rate. the experimental results show that the average classification accuracy was 98.61% for the FEI dataset and 98.21% for the Georgia Tech dataset. the average value for equal error rate was 0.68% for the FEI dataset and 0.86% for the Georgia Tech dataset. © 2024 IEEE.

关键词： Supervised learning

来源：评论

学校读者我要写书评

暂无评论

development of Iot Enabled Air Pollution Detector Using Machine learning Techniques 4

Development of Iot Enabled Air Pollution Detector Using Mach...

引用

4th international conference on Expert Clouds and Applications, ICOECA 2024

作者： Suresh Kumar, N. Nagaraj, P. Karthik Goud, B. Lokesh, A. Arjun, K. Vigneshwar Reddy, G. Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Virudhunagar India

ISBN: (数字)9798350385793

ISBN: (纸本)9798350385793

Air pollution detectors are essential tools for understanding, mitigating, and controlling the air pollution, human health, and climate. Despite significant technological advances, developing fully reliable and widely applicable air pollution detectors remains a challenge. this study intends to develop a smart IOT device that will calculate the AQI value and by using machine learning approach, the proposed model can predict future outcomes. the experimental results of the proposed system are highly accurate in predicting the future outcomes when compared to other existing models. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Research on Intelligent Seedling Environment Monitoring And Early-warning System Based on Machine learning Algorithm 4

Research on Intelligent Seedling Environment Monitoring And ...

引用

4th IEEE international conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Yu, Caiping Ren, Dongyan Xie, Zongzhi Guangxi Vocational Normal University School of Computer and Information Engineering China

ISBN: (纸本)9798350363586

With the rise of intelligent agriculture, the intelligent transformation of agriculture has been realised, bringing new development to agricultural production. However, in traditional agriculture, the regulation of seedling growth conditions mainly relies on manual management, and it is difficult to accurately predict and monitor complex ecological changes manually, which increases operational uncertainty and leads to economic losses brought about by low production efficiency. therefore, this study is based on the machine learning-based environmental monitoring and warning system for seedlings, introducing the hardware design, technical framework, machine learning algorithms in the random forest and convolutional neural network applications. through the experimental data, the speed and accuracy of the system in environmental abnormality detection are verified. the experimental results show that the system can effectively warn of environmental risks, provide scientific basis and reduce unnecessary losses. In the future, with the promotion and use of the system, it can greatly promote the effective combination of artificial intelligence and intelligent agriculture, and promote the sustainable development of agriculture. © 2024 IEEE.

关键词： Environmental monitoring

来源：评论

学校读者我要写书评

暂无评论

Ai-Driven Strategies for Securing Internet of Battlefield things(IoBT) 4

Ai-Driven Strategies for Securing Internet of Battlefield Th...

引用

4th IEEE international conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Kumar, Nishant Berwal, Krishan Verma, Rajesh Vishvakarma, S.K. Military College of Telecommunication Engineering Faculty of Communication Engineering MP Mhow India Iit Indore Department of Ee Indore India

ISBN: (纸本)9798331518981

1 the Internet of Battlefield things (IoBT) represents a significant advancement in modern warfare, leveraging the power of interconnected devices, sensors, and autonomous systems to enhance situational awareness, decision-making, and operational efficiency. However, the increasing complexity and scale of IoBT also introduce significant cyber security challenges, including vulnerabilities to cyber attacks such as Distributed Denial of Service (DDoS), data tampering, and adversarial artificial intelligence (AI). this paper explores AI-driven strategies for securing IoBT ecosystems, focusing on leveraging machine learning algorithms, real-time threat detection, and autonomous response systems to mitigate cyber risks. It examines the role of AI in enhancing encryption protocols, identifying anomalous behaviors across battlefield networks, and responding to threats autonomously with minimal human intervention. Additionally, the paper proposes adaptive security frameworks that utilize AI to learn from evolving threats and protect sensitive battlefield information. through a detailed analysis of current cybersecurity challenges and AI applications, this paper aims to contribute to the development of resilient, intelligent defense mechanisms capable of securing future IoBT deployments in dynamic and hostile environments. © 2024 IEEE.

关键词： Adversarial machine learning

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90页 << < 6 7 8 9 10 11 12 13 14 15 > >>

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：