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

1,848 篇 会议
865 篇 期刊文献
8 册 图书

馆藏范围

2,721 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,546 篇 工学
- 1,208 篇 计算机科学与技术...
- 1,037 篇 软件工程
- 333 篇 信息与通信工程
- 305 篇 控制科学与工程
- 233 篇 生物工程
- 184 篇 生物医学工程（可授...
- 171 篇 电气工程
- 148 篇 光学工程
- 101 篇 电子科学与技术（可...
- 92 篇 机械工程
- 88 篇 安全科学与工程
- 88 篇 网络空间安全
- 81 篇 化学工程与技术
- 76 篇 交通运输工程
- 66 篇 仪器科学与技术
875 篇 理学
- 457 篇 数学
- 268 篇 生物学
- 218 篇 物理学
- 187 篇 统计学（可授理学、...
- 105 篇 化学
- 78 篇 系统科学
483 篇 管理学
- 291 篇 管理科学与工程(可...
- 219 篇 图书情报与档案管...
- 139 篇 工商管理
190 篇 医学
- 150 篇 临床医学
- 145 篇 基础医学(可授医学...
- 110 篇 公共卫生与预防医...
- 81 篇 药学(可授医学、理...
79 篇 法学
- 68 篇 社会学
60 篇 农学
59 篇 经济学
- 59 篇 应用经济学
34 篇 教育学
16 篇 文学
3 篇 哲学
2 篇 历史学
2 篇 军事学
2 篇 艺术学

主题

227 篇 accuracy
162 篇 deep learning
132 篇 machine learning
128 篇 training
116 篇 real-time system...
101 篇 convolutional ne...
96 篇 feature extracti...
88 篇 predictive model...
78 篇 computational mo...
72 篇 support vector m...
67 篇 medical services
64 篇 machine learning...
64 篇 data models
58 篇 optimization
55 篇 internet of thin...
55 篇 semantics
51 篇 artificial intel...
47 篇 reliability
43 篇 image segmentati...
42 篇 reviews

机构

47 篇 college of compu...
39 篇 lamarr institute...
39 篇 nitte meenakshi ...
36 篇 department of ar...
32 篇 school of comput...
27 篇 lovely professio...
25 篇 engineering rese...
23 篇 key lab. of mach...
23 篇 department of co...
23 篇 division of arti...
22 篇 center for machi...
22 篇 department of ar...
21 篇 school of artifi...
20 篇 the lamarr insti...
20 篇 key laboratory o...
20 篇 machine learning...
20 篇 hubei provincial...
19 篇 east west instit...
19 篇 department of co...
19 篇 school of comput...

作者

39 篇 piyush kumar par...
38 篇 pareek piyush ku...
37 篇 mohsen guizani
36 篇 prateek verma
30 篇 lv jiancheng
27 篇 stachniss cyrill
24 篇 behnke sven
23 篇 guizani mohsen
23 篇 müller klaus-rob...
22 篇 li zengyang
21 篇 verma prateek
21 篇 wang liwei
20 篇 liang peng
20 篇 zhang kun
19 篇 behley jens
18 篇 von lilienfeld o...
17 篇 samek wojciech
16 篇 liu yang
16 篇 cyrill stachniss
16 篇 kersting kristia...

语言

2,296 篇 英文
420 篇 其他
6 篇 中文
1 篇 德文

检索条件"机构=Computer Science with Artificial Intelligence and Machine Learning"

共 2721 条记录，以下是151-160 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：

Optimizing Travel Itineraries: A Multi-Objective machine learning Model Approach 3

Optimizing Travel Itineraries: A Multi-Objective Machine Lea...

引用

3rd International Conference on Applied artificial intelligence and Computing, ICAAIC 2024

作者： Roy, X Samuel Issac, Titus Terrance, J Sebastian Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Tamil Nadu Coimbatore India Karunya Institute of Technology and Sciences Division of Artificial Intelligence and Machine Learning Tamil Nadu Coimbatore India

ISBN: (纸本)9798350375190

A travel itinerary is a complex problem that involves multiple objectives and constraints, such as cost, time, transportation modes, and comfort levels. This research study focuses on creating a real-time eco-friendly itinerary generator by integrating machine learning techniques. This research work explores two machine-learning algorithms: artificial Neural Networks (ANNs) and Multi-Layer Perceptron (MLP). These algorithms are evaluated for their suitability in generating user-friendly and environment-friendly itineraries. Through experimentation, the accuracy and precision of the proposed models are assessed, leading to the identification of an optimal travel planner model. The ultimate goal of this model is to provide a detailed itinerary that considers prominent modes of transportation while addressing the pressing environmental crisis. By prioritizing eco-friendly options, this approach sets itself apart from conventional travel planning tools. © 2024 IEEE.

关键词： Multilayer neural networks

来源：评论

学校读者我要写书评

暂无评论

A Review on the Applications of Natural Language Processing in Healthcare 4

A Review on the Applications of Natural Language Processing ...

引用

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

作者： Warbhe, Mohan K. Verma, Prateek Faculty of Engineering and Technology Department of Computer Science and Design Sawangi Maharashtra Wardha442001 India Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Sawangi Maharashtra Wardha442001 India

ISBN: (纸本)9798331529635

In healthcare, Natural Language Processing (NLP) is a technique to improve clinical decision support, patient care, and medical research. By automating clinical recording, NLP enhances the calibre of medical records and professional communication. It makes Electronic Health Records (EHRs) easier to use by facilitating quick and easy data entry, retrieval, and access to vital patient data that helps with precise diagnosis and efficient treatment planning. Through the analysis of patient-specific data, NLP supports clinical decision support by delivering prompt recommendations. Chatbots and virtual assistants managing repetitive duties like booking appointments also improve patient connection. NLP makes it easier to analyse vast amounts of literature for medical research, facilitating the extraction and summary of important discoveries. Healthcare data processing requires text preparation, sentiment analysis, Named Entity Recognition (NER), semantic parsing, and Natural Language Generation (NLG). However, there are obstacles to overcome, like bias, ethical concerns, system integration, privacy, and data quality. The healthcare industry can use NLP to enhance patient outcomes, promote personalized medication, and streamline healthcare delivery by guaranteeing interoperability and setting standards. © 2024 IEEE.

关键词： Challenges of NLP in Healthcare Future treads of NLP for healthcare Healthcare NLP

来源：评论

学校读者我要写书评

暂无评论

CampusSight—College Management Automation Using Full Stack and RPA 12th

CampusSight—College Management Automation Using Full Stack ...

引用

12th International Conference on Recent Trends in Computing, ICRTC 2024

作者： Manohar, Eashaan Duraimurugan, N. Vijay, K. Narayana, K.E. Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India Department of Artificial Intelligence and Machine Learning Rajalakshmi Engineering College Chennai India Department of Information Technology Rajalakshmi Engineering College Chennai India

ISBN: (纸本)9789819789450

The college management diaspora encapsulates various stakeholders such as students, faculty members, administrative personnel, and other staff. Unfortunately, most of the management workflows are undertaken manually, leading to silos, long paper work and admin overhauls. The pivotal aim of this research project is to digitalize the college management by bringing the entire setup into an intelligent application, leveraging key technologies like Automation, data analytics, full stack development. This application ultimately streamlines cumbersome tasks and enhance working across the college environment, promoting transparency and facilitating seamless interfaces for the entire user base. Swapping the monotonous manual workings with state-of-art digital platform will elevate the overall student experience by bringing down the high latency issue with the manual undertakings. Prime features of the application features management in terms of attendance, absences, on-duty requests, result disbursement, course registration, and facilitation of placement processes. Also, the system will promote enhanced organizing of events related to campus, industrial visits, increasing the net student engagement within the college and opening new opportunities. The system prioritizes core functionalities such as maintaining clean design and nimble experience, aligning with the increasing trend of digital transformation, granting greater college management autonomy. The application not only brings down the complexities prevailing in the existing college administration but also helps the higher education and placement processes alike, by leveraging key concepts like Data Analysis, machine learning and artificial intelligence from the data and insights stored, thereby adopting agile college management practices and emphasizing rapid digital growth, contributing to the entire education community. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Students

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

Scheduling the Tasks in Cloud Computing using Adaptive Adjustment in Whale Optimization Algorithm 2

Scheduling the Tasks in Cloud Computing using Adaptive Adjus...

引用

2nd International Conference on Data science and Information System, ICDSIS 2024

作者： Pareek, Piyush Kumar Nithyashree, G.D. Rajashekhar, S.A. Zanke, Pankaj Navyashree, K.S. Nitte Meenakshi Institute Of Technology Artificial Intelligence And Machine Learning Bengaluru India East West Institute Of Technology Department Of Computer Science And Engineering Bengaluru India Sapiens International Corporation United States

ISBN: (纸本)9798350381665

One of the most popular infrastructures for employing virtual machines, also known as processing units, is cloud computing. Task scheduling is fundamental problems of cloud computing. A number of methods to handle the nondeterministic polynomial-time (NP)-complete optimisation issue of choosing the best scheduling criteria in cloud computing have been proposed by academics in the past. An effective optimisation approach is suggested in this research, based on the whale optimisation algorithm (WOA), to address the common problems of solution algorithms, which include poor global optimisation ability, ease of sliding into local optimisation, and sluggish convergence speed. We provide an adaptive adjustment method that may dynamically alter search behaviour during the whale optimisation algorithm's iterative operation. The technique described to further update the position of search individuals also uses the evolutionary approach of differential variation. The algorithm's exploration and development capacities are then balanced, and a restart approach is included to keep the system from entering local optimisation. The approach simultaneously resolves the work planning issue in the situation of rain cloud processing. When compared to other algorithms, this technique uses more resources and converges more quickly. Additionally, the evaluation function seeks for the optimal answers by taking the makespan, resource cost, and load balancing level into account. © 2024 IEEE.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

A Review on the Role of artificial intelligence in Personalized learning

A Review on the Role of Artificial Intelligence in Personali...

引用

2024 Asia Pacific Conference on Innovation in Technology, APCIT 2024

作者： Qureshi, Rukaiyya Hajare, Shital Verma, Prateek Sawangi Meghe Faculty of Engineering and Technology Department of Artificial Intelligence and Data Science Maharashtra Wardha442001 India Sawangi Meghe Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Maharashtra Wardha442001 India

ISBN: (纸本)9798350361537

This article explores the revolutionary role of artificial intelligence (AI) in personalized learning, focusing on its potential to revolutionize educational processes and improve learning outcomes. This paper provides insights into how AI technologies can be used to tailor instruction, identify learning needs, and provide specific strategies that cater to different students' psychological, cognitive, and motivational preferences. The article examines case studies and examples to demonstrate different uses of AI in personalized learning settings, such as autonomous tutoring systems, personalized education channels, and analysis based on data. However, the use of AI in education raises ethical, technological, and policy concerns that require careful study and proactive actions to assure fair access, preserve learner privacy, and eliminate algorithmic biases. Ultimately, finally, the article emphasizes AI's transformative potential in personalized learning and advocates for coordinated efforts among educators, academics, and policymakers to leverage its benefits while tackling accompanying obstacles. © 2024 IEEE.

关键词： Federated learning

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

DBROA based Convolutional Auto Encoder for European Credit Card Fraud Detection 2

DBROA based Convolutional Auto Encoder for European Credit C...

引用

2nd International Conference on Data science and Information System, ICDSIS 2024

作者： Pareek, Piyush Kumar Mohan, B.R. Vidya, E.V. Zanke, Pankaj Navyashree, K.S. Nitte Meenakshi Institute Of Technology Artificial Intelligence And Machine Learning Bengaluru India East West Institute Of Technology Department Of Computer Science And Engineering Bengaluru India Sapiens International Corporation United States

ISBN: (纸本)9798350381665

Numerous studies using bad neuronic nets (DNNs) for the objective of detecting recognition card fraud have concentrated on enhancing point prediction accuracy and limiting unwelcome biases by developing various network designs or learning models. It is crucial to reckon uncertainty together with point estimate of the training data has a significant impact on how well machine learning algorithms function, therefore data imbalance is not a minor problem. In general, the data only shows a tiny portion of false communications. The effectiveness of simple machine acquiring classifiers is significantly impacted by this. This research studies several data augmentation strategies to handle the unbalanced data problem for credit card fraud detection in order to deal with the shortage of false events. The balanced data is then sent to a Convolutional Auto Encoder (CAE) for classification, and a Developed Battle Royale optimisation algorithm (DBROA) is used to determine the model's weight in the best possible way. For the purpose of recognising credit card fraud involving European cardholders, each model includes stratified K-fold cross-validation and a real-world dataset. The results show that the suggested model is more accurate than current models. © 2024 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Predicting the Spread of Covid-19 Using machine as a Service (MaaS) Through Modified Apriori Algorithm

Predicting the Spread of Covid-19 Using Machine as a Service...

引用

International Conference on Smart Systems and Wireless Communication, SSWC 2024

作者： Sett, Samir Kumar Sett, Aishik Ghosh, Anupam Department of Computer Application Techno India Kolkata India ITC Infotech Kolkata India Department of Computer Science and Engineering and Department of Artificial Intelligence & Machine Learning Netaji Subhash Engineering College Kolkata India

ISBN: (纸本)9789819613472

The cloud computing and machine learning is one of growing technology in the field of computer science. In recent years, the word "Cloud" is like a cup of tea in our daily lives. Every day, a significant volume of data is produced by different IT sectors, banking sectors, e-commerce websites like flipkart. It provides the organization with consistency, scalability, and strong enumerating power. It also delivers eminence service by generating proper outcomes in a brief amount of time. The objective of this paper is to predict the growth of Covid-19 virus in near future using machine as a Service (MaaS) through modified Apriori algorithm. In this paper, we will obtain the working graph of the algorithm. The result is also analyzed by obtaining the graphs for confidence against lift, support against confidence. At last, a running time comparative graph for modified apriori and apriori is shown for a certain duration of time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Apriori Cloud computing Confidence Covid-19 MaaS Support

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273页 << < 12 13 14 15 16 17 18 19 20 21 > >>

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：