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

60,042 篇 会议
10,779 篇 期刊文献
34 篇 科技报告
6 册 图书

馆藏范围

70,861 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

46,363 篇 工学
- 35,729 篇 计算机科学与技术...
- 29,803 篇 软件工程
- 10,912 篇 信息与通信工程
- 6,613 篇 控制科学与工程
- 4,479 篇 电气工程
- 4,390 篇 生物工程
- 4,213 篇 电子科学与技术（可...
- 3,442 篇 生物医学工程（可授...
- 2,678 篇 光学工程
- 2,444 篇 机械工程
- 1,935 篇 仪器科学与技术
- 1,823 篇 动力工程及工程热...
- 1,775 篇 化学工程与技术
- 1,458 篇 安全科学与工程
- 1,330 篇 建筑学
- 1,230 篇 交通运输工程
24,207 篇 理学
- 14,947 篇 数学
- 5,461 篇 物理学
- 4,910 篇 生物学
- 4,487 篇 统计学（可授理学、...
- 2,681 篇 系统科学
- 1,904 篇 化学
12,323 篇 管理学
- 6,694 篇 管理科学与工程(可...
- 6,265 篇 图书情报与档案管...
- 3,890 篇 工商管理
2,792 篇 医学
- 2,451 篇 临床医学
- 2,258 篇 基础医学(可授医学...
- 1,464 篇 药学(可授医学、理...
2,182 篇 法学
- 1,827 篇 社会学
1,277 篇 经济学
- 1,275 篇 应用经济学
1,165 篇 教育学
911 篇 农学
289 篇 文学
152 篇 军事学
85 篇 艺术学
39 篇 哲学
17 篇 历史学

主题

1,771 篇 computer science
1,632 篇 accuracy
1,542 篇 computational mo...
1,475 篇 feature extracti...
1,221 篇 training
1,015 篇 deep learning
986 篇 machine learning
830 篇 data mining
824 篇 predictive model...
776 篇 semantics
750 篇 real-time system...
729 篇 support vector m...
710 篇 data models
665 篇 computer archite...
581 篇 visualization
559 篇 internet of thin...
557 篇 optimization
555 篇 convolutional ne...
542 篇 neural networks
489 篇 protocols

机构

91 篇 institute of inf...
84 篇 dept. of compute...
83 篇 north-west unive...
82 篇 dept. of compute...
81 篇 infn sezione di ...
76 篇 infn sezione di ...
69 篇 institut univers...
66 篇 università di ca...
65 篇 dept. of compute...
62 篇 national centre ...
60 篇 dept. of compute...
56 篇 dept. of compute...
54 篇 dept. of informa...
51 篇 school of automa...
44 篇 leiden universit...
42 篇 infn lnf via enr...
42 篇 in2p3 lpc campus...
39 篇 dept. of compute...
38 篇 dept. of compute...
37 篇 hokkaido univers...

作者

97 篇 ferrara g.
94 篇 ardid m.
87 篇 calvo d.
82 篇 chen a.
75 篇 gal t.
73 篇 bozza c.
62 篇 ahmad jalal
60 篇 kulikovskiy v.
54 篇 kalekin o.
41 篇 gagliardini s.
40 篇 benoit d.m.
40 篇 eddymaoui a.
40 篇 labalme m.
37 篇 díaz a.f.
36 篇 androulakis g.
35 篇 huang f.
34 篇 crawford h.j.
34 篇 cafagna f.
34 篇 de palma m.
34 篇 haungs a.

语言

68,739 篇 英文
1,407 篇 其他
524 篇 中文
108 篇 日文
63 篇 朝鲜文
11 篇 德文
7 篇 法文
6 篇 西班牙文
3 篇 葡萄牙文
2 篇 斯洛文尼亚文

检索条件"机构=Dept. of Computer Science and Data Science"

共 70861 条记录，以下是101-110 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：

Effective Machine Learning Model for Disease Recognition and Categorization of Mango Leaves

Effective Machine Learning Model for Disease Recognition and...

引用

2024 International Conference on Computational Intelligence and Computing Applications, ICCICA 2024

作者： Kumar, Sandeep Gupta, Bhupesh Grover, Richa Chhabra, Mohit Computer Science & Engineering Dept. Ambala Mullana India Panipat Institute Of Engineering & Technology Computer Science & Engineering Dept. India

ISBN: (纸本)9798350306446

Maintaining the health and production of mango farms depends on the early detection of illnesses in mango trees. Despite the vital role agriculture plays, it remains an industry receiving limited attention from the machine-learning community. A noteworthy challenge is the lack of standardized and openly accessible agricultural datasets, impeding researchers from fully leveraging the potential of advanced computational prediction tools. The study focuses on employing deep learning and image processing techniques for diagnosing prevalent mango leaf diseases in India. The goal is to enhance both the quality and quantity of agricultural production by implementing effective disease control measures upon identifying plant diseases. The automation of plant disease detection proves particularly beneficial, reducing the monitoring efforts required by large farms. Rapid identification of leaf diseases is crucial, given that leaves serve as a plant's primary source of nutrition. Notably, none of the seven different mango leaf illnesses that have been observed in India have ever been the subject of earlier research. In this study, we provide a lightweight Resnet50 model that can reliably classify healthy mango leaves and the seven discovered illnesses on mango leaves. The performance of our proposed lightweight Resnet-50 model is evaluated against many pre-trained models, such as Exception, Resnet101, and VGG16. The findings reveal that the lightweight Resnet-50 model achieves the highest testing accuracy, reaching an impressive 95%. This underscores the model's effectiveness in automating the identification of mango leaf diseases, offering a promising solution for improving agricultural practices in India. © 2024 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Evaluating Various Techniques for Twitter Sentiment Analysis for Election Results 1

Evaluating Various Techniques for Twitter Sentiment Analysis...

引用

1st International Conference on Pioneering Developments in computer science and Digital Technologies, IC2SDT 2024

作者： Mishra, Prerna Punia, Divya Sikka, Geeta Sharma, Ajay K Sikka, Kushagra NIT Delhi Dept. of Computer Science and Engineering India University of Florida Dept. of Computer Science and Engineering Gainsville United States

ISBN: (纸本)9798350365016

The Indian General Election of 2019 is proof of the rise in political content on social media platforms, reflecting user attitudes and behaviors towards the electoral process. This paper examines the collective behavior of Twitter users during the election period and assesses the feasibility of election prediction through social media analysis in India. This work presents weekly sentiment analysis on election-related Twitter content. It analyzes how social media content can be used as a reliable factor of public sentiment during elections and has recourse to be a predictive parameter alongside other factors. The simulation results show that VADER outperforms various state-of-the-art techniques with a mean absolute error of 1.345 for candidate-wise predictions, significantly outperforming Textblob (5.445), Pattern analyzer (5.135), and pre-trained BERT (28.335) while yielding similar results for party-wise and alliance-wise analyses. © 2024 IEEE.

关键词： Tweets

来源：评论

学校读者我要写书评

暂无评论

5G User Equipment (UE) Positioning and Localization Estimation using Machine Learning

5G User Equipment (UE) Positioning and Localization Estimati...

引用

2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Survase, Sanket Diwan, Raman Lal, Kumari Nidhi Kumar, Shishupal VNIT Nagpur Dept. of Computer Science and Engineering Nagpur India IIIT Nagpur Dept. of Computer Science and Engineering Nagpur India

ISBN: (纸本)9798350378092

The emergence of 5G technology has ushered in a new era of connectivity, making communications faster and cheaper. One of the main challenges of 5G networks is accuracy and efficiency, which are important for many applications such as driver less cars, smart cities and virtual reality. This research paper explores the integration of machine learning techniques to improve the accuracy and reliability of 5G infrastructure. The plan uses rich data generated by 5G networks, combining various parameters such as signal strength, flight time and angle of arrival. Machine learning algorithms are used to process this data and create good models for the correct location. The system is designed to adapt to dynamic and complex urban environments where traditional methods often encounter limitations. The main contribution of this research includes the development of a new machine learning-based distribution algorithm suitable for 5G networks, a comprehensive evaluation of performance comparison with the existing system, and evaluation of recommendations for feasibility and implementation. The results showed significant improvements in accuracy and reliability, demonstrating the potential of machine learning to revolutionize the 5G workplace. © 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

Brain-Powered Vehicles for Individuals with Disabilities Leveraging AI 4

Brain-Powered Vehicles for Individuals with Disabilities Lev...

引用

4th International Conference on Technological Advancements in Computational sciences, ICTACS 2024

作者： Jaison, T. Jisna Thambi, Priyanka E. Pinheiro, Nikita Scms School of Engineering and Technology Dept. of Artificial Intelligence & Data Science Karukutty India Kalamasery India St. Paul's College Dept. of Computer Science Kalamasery India

ISBN: (纸本)9798350387490

This paper provides a novel method for enhancing mobility and independence for people with disabilities via integrating Brain-pc interface (BCI) generation with artificial intelligence (AI) for vehicle control. The proposed device permits customers to control important vehicle features which includes steerage, braking, and acceleration the usage of their Brain indicators, captured through non-invasive EEG sensors. Preliminary checking out with diverse person agencies established an outstanding accuracy price of over ninety% in deciphering person intentions and efficaciously controlling the automobile. The device adapts to person neural styles, ensuring personalized and dynamic control, and extensively improves person autonomy and self-assurance. However, demanding situations which include sign noise, user variability, and long-time period device stability stay. This studies demonstrates the capacity for BCIs and AI to revolutionize transportation for individuals with disabilities, supplying an exceptional level of independence. Future trends will focus on improving signal clarity, improving machine stability, and addressing regulatory issues to make sure safe, real-world application. © 2024 IEEE.

关键词： Neurons

来源：评论

学校读者我要写书评

暂无评论

Estimating Surface Soil Moisture based on Remote Sensing data and Crop Yield Classification using Machine Learning 9

Estimating Surface Soil Moisture based on Remote Sensing Dat...

引用

9th International Conference on Communication and Electronics Systems, ICCES 2024

作者： Anuradha, G. Susrith, Maddi Siddhardha, Kondreddy Gnana Velagapudi Ramakrishna Siddhartha Engineering College Dept. of computer science and engineering Vijayawada India Velagapudi Ramakrishna Siddhartha Engineering College Dept. of Artificial Intelligence and Data Science Vijayawada India

ISBN: (纸本)9798350377972

Soil moisture plays a critical role in environmental monitoring and sustainable agricultural practices due to its significant impact on crop growth, water availability, and overall ecosystem health. Properly understanding and managing soil moisture is vital for efficient water usage, especially in agriculture. Traditional methods in measuring soil moisture have been confined to ground-based small-scale methods, which are high price due to high labor intensity and limited spatial coverage. This project addresses its limitation in the spatial view by integrating remote sensing data from the Sentinel-1 satellite. Sentinel-1 is particularly effective in monitoring the soil moisture as it captures data in all climate conditions. By combining the satellite data with Google Earth Engine (GEE) we create a soil moisture dataset. For analyzing the joint satellite and ground truth data, the machine learning technique using Random Forest (RF) is applied and classification of crop yield is done. © 2024 IEEE.

关键词： Soil moisture

来源：评论

学校读者我要写书评

暂无评论

YOLOv8-Based Deep Learning Approach for Real-Time Skin Lesion Classification Using the HAM10000 dataset

YOLOv8-Based Deep Learning Approach for Real-Time Skin Lesio...

引用

2024 IEEE International Conference on E-Health Networking, Application and Services, HealthCom 2024

作者： Saha, Utsha Ahamed, Imtiaj Uddin Imran, Md Ashique Ahamed, Imam Uddin Hossain, Al-Amin Gupta, Ucchash Das Dept. of Computer Science North Dakota State University FargoND United States Agricultural Data Analytics Unit North Dakota State University FargoND United States Dept. of Computer Science University of South Dakota VermillionSD United States Dept. of Applied Computer Science The University of Winnipeg Winnipeg Canada Dept. of Computer Science Liverpool John Moores University Liverpool United Kingdom

ISBN: (纸本)9798350350548

Skin cancer is a prevalent and potentially fatal disease that requires early detection for effective treatment. We trained and evaluated five YOLOv8 classification model variants (YOLOv8n-cls, YOLOv8s-cls, YOLOv8m-cls, YOLOv8l-cls, and YOLOv8x-cls) on the HAM10000 dataset, which contains 10,015 dermatoscopic images of common pigmented skin lesions. The models were trained for 30 epochs using data augmentation techniques to enhance generalization. Performance was assessed using metrics including accuracy, precision, recall, F1-score, and inference time. The YOLOv8x-cls model achieved the highest accuracy of 86.2% and precision of 82.1%, while the YOLOv8lcls model demonstrated the best balance with the highest F1-score of 77.0%. Compared to previous ensemble approaches, our single YOLOv8 models achieved superior performance with lower computational overhead. The YOLOv8n-cls variant showed the fastest inference time of 0.5 ms, making it suitable for real-time applications. Our results demonstrate the potential of YOLOv8-based models for accurate and efficient skin lesion classification, which could aid in early skin cancer detection and improve patient outcomes. © 2024 IEEE.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Based Intrusion Detection for Cybersecurity in Unmanned Aerial Vehicles Network 4

Deep Learning Based Intrusion Detection for Cybersecurity in...

引用

4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Niyonsaba, Simon Konate, Karim Soidridine, Moussa Moindze Dept. Mathematics and Computer Science Dakar Senegal

ISBN: (纸本)9798350395914

In this article, we have proposed Deep Learning techniques for cybersecurity in Unmanned Aerial Vehicles (UAVs). UAVs, also known as drones, have become versatile tools used in many applications. However, UA V cybersecurity remains a major concern due to the evolution of cyberattacks. Faced with this issue, it is important to give a contribution on intrusion detection systems (IDS) to be applied in UAVs, given that existing cybersecurity solutions still present limitations. It is in this context that we have proposed Deep Learning-based intrusion detection models such as Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) and the combination of Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) models (CNN+LSTM) and these are evaluated using the CICIDS2017 dataset. Based on their performance, the proposed models are compared with Machine Learning models to decide on the best model for intrusion detection in UAVs. Thus, the results obtained during the experiment indicate that the hybrid CNN-LSTM model obtained a high accuracy of 99.063% compared to the other models. © 2024 IEEE.

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

data Complexity and Stability Induced Predictive Distributed Learning Approach 19th

Data Complexity and Stability Induced Predictive Distributed...

引用

19th International Middle Eastern Simulation and Modelling Conference, MESM 2024

作者： Igodan, E.C. Ukaoha, K.C. Al-Akaidi, M. Dept. of Computer Science University of Benin Benin City Nigeria Dept. of Computer Science Wigwe University Isiokpo Nigeria College of Science & Computing Wigwe University Isiokpo Nigeria

ISBN: (纸本)9789492859341

The performance of most classifiers degrades because the majority of feature selection algorithms do not scale well, primarily due to the inherent characteristics in high-dimensional microarray datasets, making them eventually inapplicable. This research study proposed a novel predictive distributed FS model by sample partitioning while maintaining class distribution using data complexity and stability measures. For implementation, brain tumor microarray datasets were adopted. Six feature selection algorithms and classifiers, along with their ensemble learning methodology, were implemented. The dataset was preprocessed and the SMOTE technique applied, so as to balance the class distribution and the feature/sample size ratio. The study showed significant improvement in the proposed distributed model with an accuracy of 99.67% and demonstrated a sharp reduction both in the runtime complexity and the number of selected features respectively. © 2025 EUROSIS-ETI.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of CPI prediction for India using Statistical methods and Neural Networks 2

Comparative Analysis of CPI prediction for India using Stati...

引用

2nd International Conference for Innovation in Technology, INOCON 2023

作者： Singh, A. Shukla, B. Jos, Jibrael Dept. of Data Science Pune India

ISBN: (纸本)9798350320923

Inflation is one of the main issues affecting the world economy right now, necessitating the accurate inflation prediction for the development of tools and policies by the monetary authorities to prevent extreme price volatility. Expectations of inflation influence many financial and economic actions, and this dependence motivates economists to develop techniques for precise inflation forecasting. Nearly everyone in the economy is impacted by inflation, including lending institutions, stock brokers, and corporate financial officials. In many cases, inflation determines whether a firm will accept a particular project or if banks will make a particular loan. These different economic actors can modify their financial portfolios, strategic goals, and upcoming investments if they are able to forecast changes in inflation rates. The multiple interaction economic components that depend on inflation will be better understood by economic agents operating in a business context if inflation forecasting accuracy is improved. There are numerous techniques to forecast inflation ranging from basic statistical methods to complex neural network methods. Therefore, this paper employs LSTM model to train and analyze the Consumer Price Index (CPI) indicators to obtain inflation-related prediction results. The experimental results on historical data show that the statistical model has good performance in predicting India's inflation rate compared to deep learning methods in case of smaller dataset. © 2023 IEEE.

关键词： Economics

来源：评论

学校读者我要写书评

暂无评论

Inspiring Entrepreneurship by Spreading New Technologies and Innovative Methods that Popularise science and Art 19

Inspiring Entrepreneurship by Spreading New Technologies and...

引用

19th European Conference on Innovation and Entrepreneurship, ECIE 2024

作者： Ophir, Dan Dept. of Computer Science Ariel University Israel

ISBN: (纸本)9781917204149

In recent years a new term related to GPT (Generative Pre-trained Transformer) has become very popular among professional society members who develop and use computing applications. This trend has inspired entrepreneurship in education in the following aspects: Academic - in the computer science and Management Departments Non-academic - studies for high school pupils and for adults who wish to enrich their education. The purpose of these studies is to popularise science, technology, and art using innovative methods to make these subjects attractive. Academic entrepreneurship requires students to be innovative, namely, to create a project using their acquired professional skills. The work, called the final project, is a part of the students' academic requirements at universities. As a promoter of these projects, I have been giving the students proposals, suggestions, and inspiration for the subjects of their projects. The article mentions and describes a database with hundreds of recommendations for subjects for projects as well as projects completed by students who previously finished their final project. This project's database is used as a model for the current students. The database includes the project's hierarchical classification along with subsections, according to their theme, innovation level, and completeness, indicating their practical or theoretical properties. The following projects are a sample demonstrating the variety of the final projects, for example: "Analysing the voiceless languages", "Double buffer economic boiler", and "Creating the most consensual coalition". The second aspect of the entrepreneurship being developed is a series of lectures "The Popularisation of the science and the Art". This collection of lectures includes an innovative method for preparing and presenting the lectures, connecting attractively the way in which science and art are popularised together for an audience in a wide spectrum of society. The Power-Point presentations

关键词： Students

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 << < 7 8 9 10 11 12 13 14 15 16 > >>

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：