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

88,833 篇 会议
596 册 图书
350 篇 期刊文献
4 篇 学位论文
1 篇 科技报告

馆藏范围

89,783 篇 电子文献
3 种 纸本馆藏

日期分布

学科分类号

38,499 篇 工学
- 27,692 篇 计算机科学与技术...
- 22,640 篇 软件工程
- 9,358 篇 信息与通信工程
- 8,513 篇 控制科学与工程
- 6,066 篇 电气工程
- 4,318 篇 电子科学与技术（可...
- 3,752 篇 生物工程
- 3,744 篇 机械工程
- 2,734 篇 生物医学工程（可授...
- 2,596 篇 动力工程及工程热...
- 2,174 篇 仪器科学与技术
- 1,872 篇 光学工程
- 1,856 篇 交通运输工程
- 1,638 篇 安全科学与工程
- 1,379 篇 化学工程与技术
- 1,105 篇 网络空间安全
19,409 篇 理学
- 12,578 篇 数学
- 4,022 篇 生物学
- 3,745 篇 系统科学
- 3,691 篇 物理学
- 3,456 篇 统计学（可授理学、...
- 1,386 篇 化学
10,646 篇 管理学
- 7,039 篇 管理科学与工程(可...
- 4,283 篇 图书情报与档案管...
- 3,415 篇 工商管理
2,340 篇 医学
- 2,029 篇 临床医学
- 1,978 篇 基础医学(可授医学...
- 1,266 篇 药学(可授医学、理...
1,355 篇 法学
- 1,187 篇 社会学
1,201 篇 经济学
- 1,198 篇 应用经济学
820 篇 农学
327 篇 教育学
220 篇 文学
194 篇 军事学
48 篇 艺术学
1 篇 哲学

主题

6,017 篇 genetic algorith...
5,118 篇 heuristic algori...
4,452 篇 real-time system...
4,325 篇 accuracy
4,274 篇 algorithm design...
3,864 篇 clustering algor...
3,490 篇 machine learning...
3,412 篇 prediction algor...
3,165 篇 optimization
3,035 篇 feature extracti...
2,936 篇 signal processin...
2,801 篇 computational mo...
2,650 篇 training
2,548 篇 control systems
2,488 篇 classification a...
2,465 篇 predictive model...
2,348 篇 machine learning
2,259 篇 neural networks
2,193 篇 support vector m...
2,118 篇 hardware

机构

193 篇 chitkara univers...
103 篇 school of automa...
98 篇 school of electr...
80 篇 lovely professio...
74 篇 centre of resear...
71 篇 school of comput...
66 篇 school of comput...
47 篇 national mobile ...
46 篇 department of co...
40 篇 chitkara univers...
39 篇 department of co...
38 篇 department of la...
37 篇 school of comput...
35 篇 karnataka bangal...
33 篇 college of compu...
33 篇 school of electr...
32 篇 school of comput...
32 篇 school of inform...
32 篇 department of el...
31 篇 department of co...

作者

36 篇 lei wang
36 篇 jun wang
34 篇 jian wang
30 篇 hisao ishibuchi
29 篇 li yang
26 篇 hui wang
25 篇 yu wang
25 篇 khalgui mohamed
24 篇 li peng
23 篇 wang jing
21 篇 zhang tao
21 篇 jun zhang
20 篇 rui wang
20 篇 wang lei
19 篇 bin wang
18 篇 zhang lei
17 篇 j. relin francis...
17 篇 amandeep nagpal
16 篇 vikram kumar
16 篇 chu-sing yang

语言

87,143 篇 英文
2,203 篇 其他
516 篇 中文
7 篇 俄文
2 篇 德文
2 篇 法文
1 篇 西班牙文
1 篇 土耳其文
1 篇 乌克兰文

检索条件"任意字段=International Conference on Engineering of Reconfigurable Systems and Algorithms"

共 89784 条记录，以下是241-250 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：

Anti-Spoofing: A Bio Finger Print Recognition Method using Pattern Matching Algorithm

Anti-Spoofing: A Bio Finger Print Recognition Method using P...

引用

2025 IEEE international Students' conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Harshvardhan, A.S. Prasad, Kokkula Shiva Sindhuja Reddy, A. Rahul, N. Rutvik Varasai, P. Srinivas, B. Nalla Malla Reddy Engineering College Department of Aids Telangana Hyderabad India Nalla Malla Reddy Engineering College Department of Ece Telangana Hyderabad India

ISBN: (纸本)9798331529833

Biometric authentication plays a key role in smart environments, with finger print recognition being one of the most common methods. Fingerprint readers scan and store fingerprint data, comparing it during login attempts to verify identity. While effective, these systems are vulnerable to spoofing using materials like wax, clay, or gelatine. Criminals sometimes exploit this technology to access personal information. Two main algorithms, minutiae matching and pattern matching, are used for recognition. Minutiae matching compares unique points on fingerprints, while pattern matching analyzes surface thickness, curvature, and ridge patterns. However, injuries to the fingercan make identification challenging. Advances now integrate sensors to detect pulse and sweat glands, enhancing security. Fingerprint recognition is widely employed in legal systems for identity management, but the technology relies heavily on intact surface patterns for accurate matching. © 2025 IEEE.

关键词： Palmprint recognition

来源：评论

学校读者我要写书评

暂无评论

Keyframe Extraction Approaches for Intelligent Video Analysis 4

Keyframe Extraction Approaches for Intelligent Video Analysi...

引用

4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Sabarivasan, N. Thangavel, Senthil Kumar Amrita School of Computing Department of Computer Science and Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9798331523923

Real-time violence detection is essential for protecting the safety and security of people, especially in college campuses that are dynamic and have crowds. Manual surveillance systems are popular but inefficient as they require human attention all the time and are not capable of quickly identifying and responding to violent *** the exsisting violence detection model takes quite a time for processing the entire video. The proposed model extracts features as keyframes from the video using MobileNet V3 and K-medoids clustering. The redundancy of video data can be avoided and significant violent activities identified by isolating and analyzing critical frames from video data. This enhances the efficiency and responsiveness of surveillance systems. This work primarily contributes a customized violent activities dataset and implementing keyframe extraction algorithm for optimizing the usage of computational resources, and incorporating lightweight algorithms for seamless deployment with existing CCTV networks. The experimental results clearly demonstrate the ability of this approach to detect keyframes, thereby offering a scalable and practical solution. © 2025 IEEE.

关键词： Security systems

来源：评论

学校读者我要写书评

暂无评论

A Review of Machine Learning algorithms in Diabetes Management 4

A Review of Machine Learning Algorithms in Diabetes Manageme...

引用

4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Gayaki, Unnati Daronde, Subodh Tale, Abhay Barhate, Aditya Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Computer Science and Engineering Maharashtra Wardha India Faculty of Engineering and Technology Department of Biomedical Engineering Maharashtra Wardha India Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Artificial Intelligence and Data Science Maharashtra Wardha India Datta Meghe Institute of Higher Education and Research Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Maharashtra Wardha India

ISBN: (纸本)9798331523923

Diabetes is a prevalent and chronic disease affecting millions worldwide, posing significant challenges in its management and treatment. This review article aims to explore the current and potential future roles of machine learning (ML) in diabetes management, focusing on progress, applications, and challenges. It discusses various ML techniques, including support vector machines (SVM), logistic regression, decision trees, ensemble methods, and advanced deep learning approaches such as long short-term memory (LSTM) networks and convolutional neural networks (CNN). These methods have demonstrated benefits in analytics, patient monitoring, decision support systems, personalised treatment, and patient engagement. However, significant challenges persist, such as computational complexity, data quality, limited interoperability of systems, and ethical concerns regarding AI use in healthcare. The article addresses these challenges by fostering collaboration between AI implementers and health care professionals. This collaboration is essential to develop long-term, legally compliant, and solution-oriented frameworks that enhance patient care and diabetes management and pave the way for more efficient and ethical AI applications in healthcare. © 2025 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Applications of Artificial Intelligence and Machine Learning for Accurate Forecasting and Optimization of Renewable Energy Generation 3

Applications of Artificial Intelligence and Machine Learning...

引用

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

作者： Rajarajeswaran, Jayakumar Saveetha Institute of Medical and Technical Sciences Simats Engineering Department of Nanobiomaterials Chennai602105 India

ISBN: (纸本)9798331509675

Accurate forecasting of renewable energy production is critical for integrating variable energy sources like solar and wind into the power grid. This study explores the application of Artificial Intelligence (AI) and Machine Learning (ML) techniques to improve the accuracy and reliability of renewable energy forecasting. Historical meteorological and energy production data were preprocessed and analyzed using advanced ML algorithms, including Long Short-Term Memory (LSTM) networks, Gradient Boosting Machines (GBM), and Support Vector Machines (SVM). Results demonstrated the superior performance of LSTM networks, achieving an R-squared value of 0.96, with minimal forecasting errors. Feature importance analysis revealed solar irradiance and wind speed as key determinants of energy production. This research highlights the potential of AI-driven approaches to address the inherent variability of renewable energy sources, thereby enhancing grid stability, reducing operational costs and supporting sustainable energy integration. The findings provide actionable insights into the deployment of AI-based forecasting tools in energy management systems that help in reliable and efficient renewable energy utilization. © 2025 IEEE.

关键词： Clean energy

来源：评论

学校读者我要写书评

暂无评论

Smart Antennas and Machine Learning: Enhancing Beamforming in Wireless Communications

Smart Antennas and Machine Learning: Enhancing Beamforming i...

引用

2025 international conference on Pervasive Computational Technologies, ICPCT 2025

作者： Sudhakar, A.V.V. Sharma, Upasana Visala, K. Kumar, K. Suresh Arora, Chirag Chouhan, Kuldeep Sr University School of Engineering Department of Eee Telangana Warangal India Abes Engineering College Department of Electronics and Communication Engineering UP Ghaziabad India Vignan's Institute of Information Technology Computer Science Engineering Andhra Pradesh Vishakapatnam India Panimalar Engineering College Mba Department Varadarajapuram Chennai600123 India Kiet Group of Institutions Department of Electronics and Communication Engineering U.P Ghaziabad India Sharda University Sharda School of Engineering and Technology Department of Computer Science and Applications Greater Noida201310 India

ISBN: (纸本)9798331508685

One of the most effective and widely used technological advancements for increasing capacity, enhancing quality, and expanding coverage in wireless communications systems is the smart antenna. Smart antennas are essential for increasing the effectiveness and dependability of wireless communication systems because they make use of cutting-edge signal processing techniques. Smart antennas' beamforming capability, which concentrates signal transmission and reception in particular directions, increases signal strength, lowers interference, and expands network capacity. As wireless networks become more complicated, machine learning (ML) has become a potent tool for beamforming optimisation. ML algorithms can proactively adjust antenna characteristics by using real-time data, learning from fluctuations in the environment to optimise performance. In order to improve beamforming capabilities, this research investigates the incorporation of ML with smart antenna systems. We go over several ML techniques, such as supervised and reinforcement learning, for resource allocation, user localisation, and signal-to-noise ratio (SNR) optimisation. Additionally, we draw attention to how deep learning might enhance spatial filtering, facilitating more effective communication in 5G and beyond. The potential direction for next-generation wireless communication networks is presented by the convergence of ML and smart antennas. © 2025 IEEE.

关键词： Smart antennas

来源：评论

学校读者我要写书评

暂无评论

Smart Pavement Repair Bot with IoT and Machine Learning Integration

Smart Pavement Repair Bot with IoT and Machine Learning Inte...

引用

2025 international conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Sujitha, S. Singh, Raj Narayan, Lalith Ray, Chaudhary Manas Gupta, Nishant New Horizon College of Engineering Department of Electrical and Electronics Engineering Bengaluru India

ISBN: (纸本)9798331509828

Potholes on road surfaces pose significant challenges, leading to vehicle damage, traffic inefficiencies, and increased safety risks. Conventional pothole detection and repair methods are labor-intensive, time-consuming, and costly. This project presents an autonomous Pothole Detection and Refilling Robot that utilizes Internet of Things (IoT) and Machine Learning (ML) technologies to automate the process of pothole identification and repair. The system incorporates ultrasonic sensors for detecting road surface anomalies and a camera, integrated with ML algorithms, for visual confirmation and classification of potholes. The robot wirelessly transmits detection data via Zigbee modules to a central monitoring system, facilitating real-time updates. Upon pothole detection, the robot autonomously engages a mechanical refilling system to dispense filler material, effectively restoring the road surface. By combining IoT for data communication, sensor-based detection, and ML-based image processing, the system provides a cost-effective and scalable solution for road maintenance. This approach reduces human intervention, optimizes repair efficiency, and enhances road safety by enabling continuous, autonomous monitoring and maintenance of road infrastructure. © 2025 IEEE.

关键词： Zigbee

来源：评论

学校读者我要写书评

暂无评论

Integrated Road Safety System for Real-Time Waterlogging Detection and Traffic Management Using Google Maps API

Integrated Road Safety System for Real-Time Waterlogging Det...

引用

2025 international conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Vignesh, R. Pabitha, C. Shamritha, V. Prathija, A. Srm Valliammai Engineering College Department Of Computer Science and Engineering Chennai India

ISBN: (数字)9798331509828

ISBN: (纸本)9798331509828

Potholes, waterlogging, and possible electrical hazards have a significant impact on urban traffic safety, especially during the monsoon season. Road damage, traffic jams, car accidents, and even potentially fatal electrical leaks from damaged power lines in flooded areas are all consequences of these situations. A thorough machine learning-based method for detecting potholes in real time, determining the extent of waterlogging, and identifying electrical leaks in water is presented in this study. The device measures the risk of water accumulation, estimates pothole depth, and records road conditions using computer vision algorithms. It also finds electrical leaks in water and sends out timely alerts to reduce the risk of electrocution. Using the Google Maps API, the system automatically reroutes traffic to safer routes, reducing the amount of time that cars and pedestrians are exposed to dangerous situations. Our system provides a strong, scalable foundation for enhancing road safety and urban mobility during inclement weather by combining pothole recognition, waterlogging severity assessment, and electrical danger detection. © 2025 IEEE.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

CNN-Based Pneumonia Detection and Severity Analysis in Chest X-Ray Images for Enhanced Diagnostic Support

CNN-Based Pneumonia Detection and Severity Analysis in Chest...

引用

2025 international conference on Multi-Agent systems for Collaborative Intelligence, ICMSCI 2025

作者： Muthukumar, D. Surendiran Chowdary, Bommineni Sreekar Kumar, D. Senthil Jagadeesan, P. Mythili, B. Swapna, B. Kalasalingam Academy of Research and Education Department of computer science and Engineering Tamilnadu Srivilliputhur India Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamil Nadu Virudhunagar India Rmk College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India R.M.D. Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Vel tech Multi tech Dr.Rangarajan Dr. Sakunthala Engineering college Department of Computer Science and Engineering Tamil Nadu Chennai India Dr.M.G.R Educational and Research Institute Department of Electronics and communication engineering Chennai India

ISBN: (纸本)9798331509828

Pneumonia continues to pose a substantial global health challenge, necessitating prompt and precise diagnosis to enhance patient outcomes. In order to detect pneumonia and classify its severity into mild, moderate, and severe phases, the web-based program uses deep learning algorithms to analyse chest X-ray pictures. A Convolutional Neural Network (CNN) model that has been trained on publicly accessible datasets and achieved high accuracy is integrated into the application. Furthermore, it provides personalized health recommendation, downloadable PDF reports, and a local hospital database to facilitate users in locating nearby treatment facilities. The system utilizes Fast API for backend processing and user-friendly interfaces to enhance accessibility and efficiency. This solution underscores the potential of artificial intelligence in supporting early diagnosis and effective pneumonia management. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Effectiveness of Llama 2 in addressing career development needs: A comprehensive review 1st

Effectiveness of Llama 2 in addressing career development ne...

引用

1st international conference on Applications of AI in 5G and IOT, ICAAI5GI 2024

作者： Singh, Anuradha Sharma, Himanshu Chaudhary, Ankur Arora, Mandeep Kaur Department of CSE Noida Institute of Engineering and Technology Greater Noida India Department of ECE Noida Institute of Engineering and Technology Greater Noida India Department of Psychology Kamla Nehru College University of Delhi New Delhi India

ISBN: (纸本)9781032874036

Career guidance instruments play a vital role in guiding an individual to select the most suitable career in making career choices. This study research the future contribution of Llama 2 in enhancing the career advisory systems by including more sophisticated learning algorithms along with data analytics in the recommendation process. In the next sections, it details how Llama 2 can be useful to deliver personalized career advice as well as solve complex professional demands. The discussion also includes the effects Llama 2 had on user experience, matched recommendations, and what to expect for future professional development. © 2025 the Author(s).

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Novel Civil engineering Construction Site Safety Monitoring and Warning System based on Machine Vision 3

Novel Civil Engineering Construction Site Safety Monitoring ...

引用

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

作者： Zhang, Qiankun Cheng, Qibin Zhejiang Construction Investment Innovation Technology Co. Ltd. Zhejiang Hangzhou310000 China Zhejiang Construction Engineering Group Co. Ltd. Zhejiang Hangzhou310013 China

ISBN: (纸本)9798331509675

Machine vision is widely used in the engineering field, especially in the intelligent monitoring, safety warning and information recognition scenarios. In this study, the novel civil engineering construction site safety monitoring and warning system based on machine vision is proposed. As a pioneering research, this system realizes all-weather real-time security monitoring by combining the daytime and nighttime image processing technology. In daytime image processing scenarios, this study proposes a new image de-hazing algorithm. This algorithm models the imaging process by improving the atmospheric scattering model. At the same time, the guided filtering algorithm is used for optimization, which significantly improves the image clarity in low-visibility environments. In the night image processing scenario, this study uses infrared imaging technology and filtering algorithms for image enhancement. This operation can effectively solve the challenges of image noise and detail loss in low-light environments. As the core of the model, this study proposes a safety warning framework based on image anomaly detection to meet the special needs of construction sites. This innovative architecture includes human posture rotation detection and image color deviation anomaly recognition. Through such operations, automatic recognition and warning of dangerous behaviors are achieved. Experimental results prove the effectiveness of the recognition algorithm. © 2025 IEEE.

关键词： Machine 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 << < 21 22 23 24 25 26 27 28 29 30 > >>

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：