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

1,252 篇 会议
478 篇 期刊文献
1 册 图书

馆藏范围

1,731 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

933 篇 工学
- 731 篇 计算机科学与技术...
- 628 篇 软件工程
- 221 篇 信息与通信工程
- 163 篇 控制科学与工程
- 140 篇 电气工程
- 136 篇 生物工程
- 126 篇 生物医学工程（可授...
- 95 篇 光学工程
- 92 篇 电子科学与技术（可...
- 67 篇 网络空间安全
- 62 篇 安全科学与工程
- 59 篇 机械工程
- 55 篇 仪器科学与技术
- 50 篇 化学工程与技术
- 49 篇 交通运输工程
517 篇 理学
- 255 篇 数学
- 156 篇 生物学
- 130 篇 物理学
- 109 篇 统计学（可授理学、...
- 65 篇 化学
- 42 篇 系统科学
305 篇 管理学
- 189 篇 管理科学与工程(可...
- 138 篇 图书情报与档案管...
- 101 篇 工商管理
134 篇 医学
- 105 篇 临床医学
- 100 篇 基础医学(可授医学...
- 80 篇 公共卫生与预防医...
- 55 篇 药学(可授医学、理...
58 篇 法学
- 51 篇 社会学
45 篇 经济学
- 45 篇 应用经济学
35 篇 农学
23 篇 教育学
7 篇 文学
2 篇 艺术学
1 篇 哲学
1 篇 历史学

主题

165 篇 accuracy
114 篇 deep learning
102 篇 real-time system...
84 篇 convolutional ne...
83 篇 training
75 篇 machine learning
73 篇 feature extracti...
64 篇 predictive model...
63 篇 computational mo...
50 篇 medical services
48 篇 data models
47 篇 support vector m...
46 篇 optimization
44 篇 machine learning...
42 篇 internet of thin...
40 篇 reliability
31 篇 prediction algor...
30 篇 monitoring
30 篇 semantics
29 篇 security

机构

35 篇 nitte meenakshi ...
30 篇 department of ar...
24 篇 department of co...
23 篇 artificial intel...
21 篇 department of ar...
19 篇 east west instit...
19 篇 department of co...
19 篇 school of artifi...
18 篇 machine learning...
17 篇 department of ar...
17 篇 lovely professio...
17 篇 division of arti...
17 篇 school of comput...
16 篇 machine learning...
16 篇 college of compu...
15 篇 department of ph...
14 篇 department of el...
14 篇 machine learning...
14 篇 department of el...
13 篇 school of comput...

作者

35 篇 mohsen guizani
33 篇 piyush kumar par...
32 篇 pareek piyush ku...
23 篇 prateek verma
21 篇 stamou giorgos
21 篇 guizani mohsen
19 篇 zhang kun
15 篇 karray fakhri
14 篇 ghojogh benyamin
14 篇 verma prateek
14 篇 lymperaiou maria
13 篇 ghodsi ali
13 篇 crowley mark
12 篇 vijay k.
11 篇 xiaojiang du
11 篇 cai ruichu
10 篇 filandrianos gio...
10 篇 rushikesh burle
9 篇 liu yang
9 篇 r. santhana kris...

语言

1,529 篇 英文
199 篇 其他
3 篇 中文

检索条件"机构=Artificial Intelligence and Machine Learning School of Computer and Engineering"

共 1731 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：

Pneumonia Detection in Chest X-Rays Using Combined Approach of Deep learning 2

Pneumonia Detection in Chest X-Rays Using Combined Approach ...

引用

2nd IEEE International Conference on Networks, Multimedia and Information Technology, NMITCON 2024

作者： Aditya Pai, H. Pareek, Piyush Kumar Guruprasad, M.S. Chandrappa, S. Bhargava, Krishna Mit Art Design and Technology University Mit School of Computing Pune India Nitte Meenakshi Institute of Technology Department of Artificial Intelligence and Machine Learning Bengaluru India Department of Computer Science and Engineering Dehradun India School of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350372892

A respiratory infection like pneumonia faces a serious health challenge across the globe, especially in the poor and underdeveloped countries. The pneumonia is affected by various factors like bacteria or viruses. The reason for the affection is due to higher level of pollution, poor air quality, excess of population, poor infrastructure etc. To reduce the threat from pneumonia, there is a need for early and accurate detection of the infection by using chest X-ray images as the most effective diagnostic method. The paper proposes an automated chest X-ray analysis system by using VGG16 architecture and a weighted average ensemble method to enhance diagnostic accuracy. By integrating deep transfer learning, the system overcomes data scarcity issues, achieving a remarkable 99% accuracy on a publicly available dataset. The research underscores the potential of automated systems in improving pneumonia diagnosis, highlighting the urgent need for advanced diagnostics in resource-limited settings. © 2024 IEEE.

关键词： Air quality

来源：评论

学校读者我要写书评

暂无评论

Enhancing Web Security: An Advanced Automated Kitterman Tool for Comprehensive Network Vulnerability Detection

Enhancing Web Security: An Advanced Automated Kitterman Tool...

引用

2024 IEEE International Students' Conference on Electrical, Electronics and computer Science, SCEECS 2024

作者： Sasikumar, R. Anita, C.S. Rajalakshmi, D. Sudharson, K. Alekhya, Badi Kumar, N. Sathish R.M.D. Engineering College Department of Computer Science and Engineering Chennai India R.M.D. Engineering College Department of Artificial Intelligence and Machine Learning Chennai India

ISBN: (纸本)9798350348460

Strong security is essential in the ever-changing world of web applications to ward off potential dangers. To identify various network vulnerabilities like Cross-Site Scripting, Database Injection, Information Disclosure, Subdomain Enumeration, Cache Deception, Banner Grabbing, Technology Fingerprinting, Apache Denial-of-Service, Apache Struts Remote Code Execution, and Clickjacking, this paper presents a novel automated Kitterman tool. The application uses a powerful crawler to extract links and systematically find vulnerabilities using a URL input. Our investigation shows that our technology outperforms all previous tools with an astounding output level of 91.8%. With the proactive features of our automated Kitterman tool, you can fortify your online defences and make sure that your web applications are resilient against a wide range of possible threats. © 2024 IEEE.

关键词： automated kitterman tool cross-site scripting database injection network vulnerability detection web security

来源：评论

学校读者我要写书评

暂无评论

machine learning in Healthcare: A Review of Current Applications and Future Trends 2

Machine Learning in Healthcare: A Review of Current Applicat...

引用

2nd International Conference on machine learning and Autonomous Systems, ICMLAS 2025

作者： Yesankar, Prajyot Puri, Chetan Barahate, Aditya Gote, Pradanywant M. Hajbe, Janhavi Pawar, Adesh Department of Computer Science & Design Maharashtra Wardha442001 India Department of Artificial Intelligence & Machine Learning Maharashtra Wardha442001 India Department of Computer Science & Medical Engineering Maharashtra Wardha442001 India

ISBN: (纸本)9798331505745

machine learning (ML) has been a main force behind important breakthroughs in patient tracking, personalized medicine, medical tests, and operating efficiency in the healthcare business in recent years. machine learning algorithms provide unique insights into early disease identification, picture analysis, and prediction analytics, improving diagnosis accuracy and treatment results. These programs are able to examine big and complex information. By predicting treatment effectiveness and genetic risks, machine learning (ML) allows personalized medicine by allowing customized care through tailored therapy approaches. Furthermore, preventative health management is backed by ML-driven prediction analytics and online patient tracking, especially for chronic illnesses. Operationally, machine learning increases process efficiency and cuts costs, allowing for data- driven decision-making and individualized patient care. However, there are important ethics issues with machine learning acceptance in the healthcare business as well, such as data protection, computer bias, and legal problems. This study offers a full analysis of the state-of-the-art machine learning applications in healthcare, stressing their revolutionary potential while discussing the ethics issues and hurdles that must be addressed to ensure execution that is both responsible and fair. © 2025 IEEE.

关键词： Personalized medicine

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Image Analysis for Precision Diagnosis and Recognition Using Cutting-Edge Visual Encoding

Revolutionizing Image Analysis for Precision Diagnosis and R...

引用

2024 IEEE International Students' Conference on Electrical, Electronics and computer Science, SCEECS 2024

作者： Rajalakshmi, D. Anita, C.S. Sasikumar, R. Sudharson, K. Alekhya, Badi Rose, S. Remya R.M.D. Engineering College Department of Computer Science and Engineering Chennai India R.M.D. Engineering College Department of Artificial Intelligence and Machine Learning Chennai India

ISBN: (纸本)9798350348460

This groundbreaking study introduces a revolutionary image analysis method, showcasing unprecedented accuracy in precision diagnosis and recognition. The innovative approach seamlessly integrates feature detection and description, demonstrating exceptional proficiency in identifying crucial local features. The advanced visual encoding architecture, surpassing conventional methods, utilizes intricate convolutional layers and the renowned Haar algorithm, achieving a remarkable 99% success rate. This comprehensive suite of advancements propels image analysis to new heights, with potential applications ranging from medical diagnostics to facial recognition. Strongly accepted for its cutting-edge techniques and impressive success rate. © 2024 IEEE.

关键词： facial recognition feature detection image analysis precision diagnosis visual encoding

来源：评论

学校读者我要写书评

暂无评论

Language Models as Knowledge Bases for Visual Word Sense Disambiguation 1

Language Models as Knowledge Bases for Visual Word Sense Dis...

引用

1st Workshop on Knowledge Base Construction from Pre-Trained Language Models and the 2nd Challenge on Language Models for Knowledge Base Construction, KBC-LM + LM-KBC 2023

作者： Kritharoula, Anastasia Lymperaiou, Maria Stamou, Giorgos Artificial Intelligence and Learning Systems Laboratory School of Electrical and Computer Engineering National Technical University of Athens Greece

Visual Word Sense Disambiguation (VWSD) is a novel challenging task that lies between linguistic sense disambiguation and fine-grained multimodal retrieval. The recent advancements in the development of visiolinguistic (VL) transformers suggest some off-the-self implementations with encouraging results, which however we argue that can be further improved. To this end, we propose some knowledge-enhancement techniques towards improving the retrieval performance of VL transformers via the usage of Large Language Models (LLMs) as Knowledge Bases. More specifically, knowledge stored in LLMs is retrieved with the help of appropriate prompts in a zero-shot manner, achieving performance advancements. Moreover, we convert VWSD to a purely textual question-answering (QA) problem by considering generated image captions as multiple-choice candidate answers. Zero-shot and few-shot prompting strategies are leveraged to explore the potential of such a transformation, while Chain-of-Thought (CoT) prompting in the zero-shot setting is able to reveal the internal reasoning steps an LLM follows to select the appropriate candidate. In total, our presented approach is the first one to analyze the merits of exploiting knowledge stored in LLMs in different ways to solve WVSD. © 2023 CEUR-WS. All rights reserved.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

Intelligent Management Information System: Web Approach 15

Intelligent Management Information System: Web Approach

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Sujatha, E. Devi, S. Renuka Subha, S. Sree Raju, D. Naveen Loganathan, V. Chennai India Department of Artificial Intelligence and Machine Learning Rajalakshmi Engineering College Chennai India Department of Computer Science and Engineering R.M.K. Engineering College Kavaraipettai Chennai India

ISBN: (纸本)9798331300579

Aims to develop web application for information management and sharing which helps educational institutions broadcast information to the students and their faculties. A college generates and uses a large amount of data where it needs to be stored in the centralized repository. This data must be communicated appropriately from the authorities to students, faculty, and HOD. This web application resolves to store, manage, and distribute this information. It is intended for information management and sharing in a way that can manage and manipulate data in a centralized place which helps us reduce the time required for updating, storing, sharing the information a college is generating. And eliminates duplication and maintains consistency in data and using one of the latest and powerful concepts called session which helps us store the user information across multiple web pages. The goal of the of web application for information management and sharing is to achieve centralized data management and accessibility. © Grenze Scientific Society, 2024.

关键词： Information hiding

来源：评论

学校读者我要写书评

暂无评论

Customer Behaviour Analysis: Tools Overview 2

Customer Behaviour Analysis: Tools Overview

引用

2nd IEEE International Conference for Women in Innovation, Technology and Entrepreneurship, ICWITE 2024

作者： Bharti, Jigyasa Dongre, Snehlata Thorat, Mayuri G H Raisoni College of Engineering Dept. of Computer Science and Engineering Nagpur India PES's Modern College of Engineering Dept. of Artificial Intelligence and Machine Learning Pune India

ISBN: (纸本)9798350383287

Analytics is a process of collecting and analyzing data that can help in taking meaningful decisions. The data is collected from various sources, this raw data is then processed and converted to dashboards which assists in business analyzation. Analytics are of various types such as descriptive, diagnostic, predictive, prescriptive and text. One area of analytics is Business intelligence which is a broader concept of using various tools and methods that involves presentation of business data to support decision making. Customer behavioral analysis can be conducted by having insights from web analytics. It is a process of understanding how a customer is responding to a website. Regular improvements can be done to increase customer interaction, enhance user experience and data-driven decision-making. In this paper, we will be discussing two major tools that are used for behavior analysis. © 2024 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Improving Software Defects Detection: An In-Depth Analysis of machine learning Methods and Static Analysis Tools for Greater Accuracy 2

Improving Software Defects Detection: An In-Depth Analysis o...

引用

2nd International Conference on machine learning and Autonomous Systems, ICMLAS 2025

作者： Bobade, Veer Puri, Chetan DMIHER Faculty of Engineering And Technology Department of Artificial Intelligence and Machine Learning Maharashtra Wardha India DMIHER Faculty of Engineering And Technology Department of Computer Science and Engineering Maharashtra Wardha India

ISBN: (纸本)9798331505745

Enhancing software quality and reducing testing expenses requires better software fault detection. To guarantee the dependability and usability of software, Software Defect Prediction (SDP) uses machine learning approaches to anticipate and address any problems early in the development cycle. Numerous machine learning techniques, such as Support Vector machines (SVM), Random Forest (RF), Logistic Regression, Naïve Bayes, Multilayer Perceptron (MLP), Decision Stump, J48, Lazy IBK, and ZeroR, are thoroughly examined in this work. With an emphasis on feature selection as a crucial step in increasing prediction accuracy and lower computing costs, these approaches are assessed for their capacity to detect software flaws precisely. This research study demonstrates how these models may improve fault identification and prevention procedures using historical records from sources such as the PROMISE repository. The study highlights the best practices for machine learning-based software quality assurance, lowering expenses while guaranteeing superior results. © 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

A Review of machine learning Algorithms for Detection of Breast Cancer 4

A Review of Machine Learning Algorithms for Detection of Bre...

引用

4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Tale, Abhay Barhate, Aditya Verma, Prateek Gourshettiwar, Palash Faculty of Engineering and Technology Department of Artificial Intelligence and Data Science Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Computer Science and Medical Engineering Maharashtra Wardha442001 India

ISBN: (纸本)9798331529635

Breast cancer is still a global health concern, chiefly affecting women, as it is one of the major causes of cancer mortality. For the therapy to be effective, early diagnosis of cancer is critical to raising the survival level and increasing the effectiveness of the procedure. The advancement in the applied technique of machine learning (ML) has brought further opportunities for early and effective diagnosis of breast cancer. This review paper provides insights into how different ML algorithms including the Support Vector machine (SVM), Convolutional Neural Network (CNN), Random Forests, and many more have contributed to the detection of breast cancer. These algorithms have proved effective in providing solutions to various medical data and imaging including early diagnosis and treatment. The paper also looks at the use of ML with precision medicine to show that these technologies will help minimize false diagnoses and offer better treatment options. This review consolidates recent works and advancements to emphasize the prospect of ML in breast cancer management and calls for more studies to enhance its implementation in practice © 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

Comparing machine learning Algorithms for Real-Time Forest Fire Detection using Color, Motion, and Shape Features 5

Comparing Machine Learning Algorithms for Real-Time Forest F...

引用

5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Dixit, Rinku Sharma Choudhary, Shailee Lohmor Mahaveerakannan, R. Kaveya, E. New Delhi Institute of Management Department of Artificial Intelligence and Machine Learning Delhi110062 India Saveetha School of Engineering Department of Computer Science and Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai India

ISBN: (纸本)9798331518097

Forest fires are extremely dangerous to ecosystems, animals, and humans;thus, it is crucial to detect them early on to limit the harm they cause. Presenting a novel framework for the detection of forest fires is the objective of this study. To increase detection speed and accuracy, this framework mixes colour, motion, and form information with machine learning algorithms. To capture the dynamic nature of fire - its ever-changing hues, distorted forms, and unending motion - an iterative method is employed. Colour probabilities are determined during the segmentation stage before going to the verification step. The categorisation stage and subsequent picture processing both make use of colour histograms. These characteristics allow the system to distinguish between flames and other things more effectively. Evaluating the framework's efficacy involved using intersection over union (IoU) ratios and frame-based evaluation. While IoU is used to test the system's ability to localise the fire inside an image, frame-based assessment is used to test the accuracy of fire detection. Tests on the VisiFire dataset proved the framework's dependability with an 89.97% true-positive rate and a 10.03% false-negative rate. And with an average frame rate of 21.70 FPS, the system is fast enough for real-time processing workloads. Considering these results, it seems like the suggested approach could greatly enhance forest fire early warning capabilities. It can also maintain a high degree of accuracy while providing quicker response times. Protecting forest ecosystems, reducing human life danger, and improving disaster management are all possible outcomes of integrating this technology into early warning systems. This framework is a huge step forward in the world of modern fire detection systems. © 2024 IEEE.

关键词： Fire detectors

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174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：