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

64,565 篇 会议
597 册 图书
326 篇 期刊文献

馆藏范围

65,487 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

38,377 篇 工学
- 35,097 篇 计算机科学与技术...
- 23,067 篇 软件工程
- 8,726 篇 信息与通信工程
- 5,271 篇 电气工程
- 4,761 篇 生物工程
- 4,757 篇 控制科学与工程
- 3,813 篇 生物医学工程（可授...
- 1,632 篇 网络空间安全
- 1,578 篇 安全科学与工程
- 1,451 篇 光学工程
- 1,326 篇 机械工程
- 1,256 篇 动力工程及工程热...
- 1,242 篇 电子科学与技术（可...
- 1,192 篇 仪器科学与技术
- 1,187 篇 化学工程与技术
14,082 篇 理学
- 7,955 篇 数学
- 5,257 篇 生物学
- 3,617 篇 统计学（可授理学、...
- 3,113 篇 系统科学
- 2,334 篇 物理学
- 1,213 篇 化学
8,772 篇 管理学
- 5,070 篇 管理科学与工程(可...
- 4,398 篇 图书情报与档案管...
- 2,233 篇 工商管理
4,424 篇 医学
- 3,697 篇 临床医学
- 3,227 篇 基础医学(可授医学...
- 2,071 篇 药学(可授医学、理...
- 1,730 篇 公共卫生与预防医...
1,854 篇 法学
- 1,604 篇 社会学
1,181 篇 农学
- 1,154 篇 作物学
991 篇 经济学
733 篇 教育学
338 篇 文学
45 篇 艺术学
39 篇 军事学
5 篇 哲学
5 篇 历史学

主题

17,119 篇 machine learning
5,347 篇 machine learning...
4,566 篇 deep learning
4,067 篇 accuracy
3,975 篇 support vector m...
3,446 篇 computational mo...
3,311 篇 training
3,214 篇 predictive model...
2,928 篇 feature extracti...
2,026 篇 data models
1,949 篇 cloud computing
1,764 篇 real-time system...
1,713 篇 neural networks
1,600 篇 adversarial mach...
1,551 篇 prediction algor...
1,311 篇 artificial intel...
1,302 篇 data mining
1,282 篇 decision trees
1,198 篇 random forests
1,150 篇 internet of thin...

机构

203 篇 chitkara univers...
134 篇 school of comput...
80 篇 karnataka bangal...
78 篇 school of comput...
66 篇 department of co...
48 篇 chennai
48 篇 lovely professio...
44 篇 univ chinese aca...
44 篇 centre of interd...
42 篇 school of comput...
40 篇 graphic era deem...
37 篇 graphic era deem...
35 篇 shenyang institu...
31 篇 department of co...
30 篇 department of in...
30 篇 faculty of compu...
29 篇 department of co...
29 篇 shanghai jiao to...
29 篇 vishwakarma inst...
28 篇 computer science...

作者

36 篇 anjali t.
28 篇 de-shuang huang
26 篇 isman kurniawan
24 篇 rakesh kumar
23 篇 kumar anil
22 篇 hui wang
21 篇 amandeep nagpal
21 篇 kumar ajay
21 篇 gill kanwarparta...
20 篇 qin zengchang
20 篇 sharif mhd saeed
19 篇 yu wang
19 篇 ajay kumar
18 篇 qomariyah nunung...
18 篇 pareek piyush ku...
17 篇 zohreh doborjeh
16 篇 schuurmans dale
16 篇 andersson karl
16 篇 kumar manish
15 篇 shiva mehta

语言

55,297 篇 英文
10,017 篇 其他
635 篇 中文
3 篇 法文
2 篇 葡萄牙文
2 篇 俄文
1 篇 西班牙文
1 篇 土耳其文

检索条件"任意字段=International Conference on Machine Learning and Computing"

共 65488 条记录，以下是4591-4600 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：

Detecting Radioactive Mineralization using DBSCAN and BIRCH Algorithms 6

Detecting Radioactive Mineralization using DBSCAN and BIRCH ...

引用

6th international conference on computing and Informatics, ICCI 2024

作者： Jahlan, Ali Othman Youssef, Mohamed A.S. Mohammed, Ammar Computer Science Department FGSSR Cairo University Giza Egypt Exploration Division Nuclear Materials Authority P.O. Box 530 Maadi Cairo Egypt Faculty of Computer Science MSA university Giza Egypt FGSSR Cairo University Egypt

ISBN: (纸本)9798350373875

This study focuses on Airborne Gamma Ray Spectrometry (AGRS) Surveying data to identify naturally existing zones with radioactive anomalies, such as potassium, uranium, and thorium, in the Wadi-Biyam and its surroundings in Egypt's Eastern Desert. The AGRS produces raw and unlabeled data collected from the background radiation and radiation emitted by the radioactive elements. Using anomaly detection statistical methods with the data produced by AGRS faces various challenges, such as inaccuracy, time consumption, bias, limited scope, and false certainty. These issues can lead to costly and hazardous outcomes, so there is a need for an innovative approach to deal with these issues. We apply two machine learning methods for anomaly detection, DBSCAN and BIRCH, with the Silhouette Coefficient to evaluate the result and mineral zone planning. Two of the nine rock types have high concentrations of radioactive elements: younger granite and wadi deposits. © 2024 IEEE.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

SQL Injection Detection in Cloud computing with machine learning Algorithms 23

SQL Injection Detection in Cloud Computing with Machine Lear...

引用

6th international conference on Networking, Intelligent Systems and Security, NISS 2023

作者： Hadji, Abdelhakim Raouyane, Brahim Rachdi, Mohamed Department of Mathematics and Computer Science Faculty of Sciences Ain Chock Computer Sciences and Systems Laboratory Hassan Ii University of Casablanca Casablanca Morocco Isga Casablanca Morocco

ISBN: (纸本)9798400700194

Due to the coronavirus crisis, a lot of companies all over the world started a fast digitalization of their business and became more comfortable with the digital world. In this way, a lot of people in the digital domain, including net developers and system engineers, are exposed to different types of risks that they may not completely know or understand. SQL injection is one such vulnerability that can be exploited by attackers to inject malicious data into a database via an application programming interface (API) call request that uses SQL syntax. Cloud computing (IaaS) and network as a service (Naas) provide companies with a wide range of advantages. However, the same advantages can also pose certain vulnerabilities to the organization. In this paper we will focus on SQL injection attacks and make a comparison between different machine learning algorithms that can be used to detect SQL injection attacks, such as "Naive Bayes"and "K-NN", SVN, and decision tree, we will also use a deep learning algorithm CNN, this comparison will show the potential that machine learning algorithms can offer in terms of cloud security. © 2023 ACM.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

A Trusted Mechanism for Participant Screening and Verification in Federated learning 4

A Trusted Mechanism for Participant Screening and Verificati...

引用

4th international conference on machine learning and Intelligent Systems Engineering (MLISE)

作者： Xie, Yun Wu, Yucheng Wang, Hongyan Li, Ang Nanjing Vocat Coll Informat Technol Jiangsu Prov Serv Customizat Network Applicat Eng Nanjing Peoples R China Nanjing Vocat Coll Informat Technol Nanjing Peoples R China Nanjing Univ Posts & Telecommun Nanjing Univ Sci & Technol Zijin Coll Nanjing Peoples R China

ISBN: (纸本)9798350375084;9798350375077

Federated learning(FL) solves the problem of "Data Silos" achieving the dual-purpose of data retention and remote sharing, which is widely applied in fields such as healthcare, transportation, and manufacturing. Local participants (LPs) are the main entities in FL, contributing resources such as data, computing, communication, and energy. The actual contribution of LPs directly affects the performance of federated learning. Existing research has mostly focused on how to design efficient algorithms for LPs, while neglecting the credibility of them. Obviously, highly trusty LPs will provide high-quality data sources and model medium parameters, which are the core factors affecting the performance of FL. This paper designs a new mechanism based on the joining protocol to verify the legitimacy of LPs, and combines subjective logical models to evaluate the reputation of participants. It solves the credibility evaluation and screening problems of participants, as well as the fairness of rewards.

关键词： Federated learning Reputation mechanism Subject logic Join protocol

来源：评论

学校读者我要写书评

暂无评论

Dataset Generation for Stuck-at-Fault Detection in Array Multiplier Circuit using Multi-fold Classification 15

Dataset Generation for Stuck-at-Fault Detection in Array Mul...

引用

15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Saisanjna, C. Jedar, Pratiksha S. Prathiksha, M.V. Shruthi, M.L.J. PESUniversity Department of Electronics and Communication Engineering Bengaluru560085 India

ISBN: (纸本)9798350370249

Faults are the defects in circuits that are also referred to as unexpected scenarios occurring in digital circuits. These give rise to errors or operations that result in unreliable outcomes. Thus, the detection of these faults is an important task that otherwise marks a compromise on acceptance of the circuits. Though automatic test pattern generators are the rescuers aiding in generating test patterns, the intervention of machine learning can leverage a better methodology to progress. This paper concentrates on the development of a dataset capable of classifying single stuck-at-faults in a 16×16 array multiplier. The dataset generated is for a fourfold fault classification technique to reduce the number of classes in each stage. The data is created using ATALANTA® software. The strategy has reduced the number of classes to 16 in the first fold, 15 in the second fold, 14 in the third fold, and 2 in the fourth fold as opposed to around 6000 classes if multi-fold was not incorporated. © 2024 IEEE.

关键词： ATALANTA Automatic Test Pattern Generation Digital circuits machine learning Stuck-at-fault Test pattern Test vectors

来源：评论

学校读者我要写书评

暂无评论

Enhancing railway operations: machine learning approaches for stopping distance prediction 15

Enhancing railway operations: machine learning approaches fo...

引用

15th international conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Kumar, Abhishek Khajuria, Raghav CRL-BEL Ghaziabad India

ISBN: (纸本)9798350370249

Ensuring railway safety systems advance is vital for protecting passengers, pilots, and assets. This study concentrates on creating an automatic braking system for Indian Railways to improve safety by accurately forecasting stopping distances during braking maneuvers. Utilizing the Indian Railways dataset, a thorough analysis of braking data is conducted, emphasizing instances of loco pilot intervention in brake deployment, covering normal braking scenarios and emergencies triggered by the Kavach system. The proposed approach entails filtering the dataset to identify braking instances where loco pilot intervention affects brake application. Subsequently, machine learning regression techniques are utilized to forecast stopping distances based on the filtered brake deployment data. Various regression methods, including linear, polynomial, support vector, and random forest regression, are applied and assessed for their efficacy in accurately predicting stopping distances. The outcomes of this research not only aid in the development of an automatic braking system for Indian Railways but also offer valuable insights into selecting optimal regression methods for forecasting stopping distances in real-world railway operations. ©2024 IEEE.

关键词： Support vector regression

来源：评论

学校读者我要写书评

暂无评论

AI-Powered Trash Classification System for Lakes and Water Bodies Using Transfer learning 3

AI-Powered Trash Classification System for Lakes and Water B...

引用

3rd international conference on Power, Control and computing Technologies, ICPC2T 2024

作者： Kundu, Sumit Sharma, Mehul Pillai, Anju S Amrita School of Engineering Department of Electrical and Electronics Engineering Amrita Vishwa Vidyapeetham Coimbatore India

ISBN: (纸本)9798350349207

The growing accumulation of rubbish in lakes and bodies of water poses a huge environmental concern that necessitates creative solutions. To address this issue, the study proposes an artificial intelligence (AI) powered trash classification system based on transfer learning. This system seeks to revolutionize waste management in lakes and water bodies by leveraging AI and machine learning (ML) technology. The methodology integrates computer vision, advanced ML algorithms, and robotics to identify, classify, and collect various sorts of trash in bodies of water. The system incorporates a pre-Trained residual network (ResN et-50) model. Extensive simulations are carried out, and the experiments show that transfer learning using ResN et50 can obtain great results in classifying garbage photos into numerous categories. With an accuracy of 95.6%, the model offers a promising deep-learning option for automated waste management systems. The model's strong precision and recall scores demonstrate its ability to classify various waste types in real-world contexts correctly. © 2024 IEEE.

关键词： Lakes

来源：评论

学校读者我要写书评

暂无评论

Enhancing Accessibility of Feedback Collection in ML Models Through Keyword Spotting: A Moroccan Darija Model 6

Enhancing Accessibility of Feedback Collection in ML Models ...

引用

6th international conference on Intelligent computing in Data Sciences, ICDS 2024

作者： Miftah, Rim Ibork, Yassine Mourhir, Asmaa School of Science and Engineering Al Akhawayn University Ifrane Morocco

ISBN: (纸本)9798350351200

This paper presents an innovative approach to enhancing feedback collection accessibility in machine learning models through the development of a keyword spotting system (KWS) designed for Moroccan Darija, a low-resource dialect. The solution allows blind and visually impaired users to give feedback on model outputs using voice commands, providing a hands-free method to indicate misclassification by saying 'Mas7i7ch' (incorrect) or confirmation by saying 'S7i7' (correct). Data collection involved gathering over 500 distinct audio samples in different environments, which formed the basis of the model training. The KWS model achieves 97.3% accuracy and 97% F1 score. We leveraged the KWS as part of the Human-AI Interaction of a machine learning application to collect user feedback about model predictions and misclassifications through voice commands. To evaluate our system's real-world applicability, a comprehensive user evaluation was conducted with over 112 participants of diverse genders, ages, vision conditions, and intellectual backgrounds. The system achieved a high accessibility rating of 88.4%, highlighting its effectiveness in improving inclusion and providing an intuitive voice-based interface for blind and visually impaired individuals. © 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

Flask Powered Heart Health Predictor Using machine learning Algorithms 2

Flask Powered Heart Health Predictor Using Machine Learning ...

引用

2nd IEEE international conference on Contemporary computing and Communications, InC4 2024

作者： Bhavani, Dhanunjay Reddy, Kattekommula Farid Kumar Ananthula, Sai Manish Soundararajan, Surendhar Shanmugasundaram, Hariharan Kukreja, Vinay Vardhaman College of Engineering Department of Computer Science and Engineering Hyderabad India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350383652

Heart Health Predictor Using Flask is an innovative web application that integrates Flask as its front end and Python as its back end. Ideal for healthcare professionals and individuals, it forecasts heart disease risk through a seamless fusion of Flask for data input and Python for machine learning. With cardiovascular disease claiming a life every minute, automating prediction becomes crucial. In medical care, information science manages vast data, addressing the complexity of coronary disease prediction. Utilizing a cardiac disease dataset from the UCI AI repository. The research presented here employs AI algorithms - Light GBM, AdaBoost, Gradient Boosting, XG Boost, and Random Forests - to predict and categorize the likelihood of coronary sickness. The study, providing a relative report on algorithm performance, reveals Light GBM's exceptional accuracy of 90%, making it a promising solution for enhancing predictive capabilities in heart health. © 2024 IEEE.

关键词： Diseases

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of machine learning Algorithms Through Visualizations 8

Comparative Analysis of Machine Learning Algorithms Through ...

引用

8th IEEE international conference on Recent Advances and Innovations in Engineering, ICRAIE 2023

作者： Ismail, Mohammad Hafiz Razak, Tajul Rosli Noor, Noorfaizalfarid Mohd Aziz, Azlan Abdul Universiti Teknologi MARA College of Computing Informatics and Mathematics Arau Malaysia Universiti Teknologi MARA College of Computing Informatics and Mathematics Shah Alam Malaysia

ISBN: (纸本)9798350315516

This paper presents a visualization technique designed to simplify the process of comparing machine learning classification results and subsequently improving interpretability. The main goal of this study is to construct an end-user interface capable of visualizing the outcomes of classification results generated by multiple machine-learning algorithms. To accomplish this, we conduct an empirical study that assesses the performance of machine learning algorithms on both the standard Iris dataset and a real-world zakat financial aid dataset. Our research involves an examination of the behavior of machine learning algorithms on the Iris dataset, providing practical insights into their functionality. We specifically focused on J48, PARTS, and Random Tree, chosen for their ease of implementation as ruleset in various programming languages. Additionally, we incorporated Neural Network into our study, considering its growing popularity in deep learning and deep neural network research. The interface incorporates interactive charting functionality to visually represent the outcome of each machine learning models. Based on the implementation, the proposed methodology has shown potential in aiding visual comparisons of machine learning algorithms, showcasing both interactivity and usability. The methodology could also prove beneficial for research aiming to optimize user-interface elements that represent input features, addressing concerns about overcrowding users' screens. © 2023 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Application to Enhance the Programming Knowledge of Children 6

Application to Enhance the Programming Knowledge of Children

引用

6th international conference on Advancements in computing, ICAC 2024

作者： Dissanayake, Anuga Lakpriya, Vishwa Sanjeevan, Mahendran Fahmi, Ahamed Siriwardana, Samanthi E.R. Samaraweera, Mihiri Sri Lanka Institute of Information Technology Dept. of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798331517878

This proposal outlines the development of a comprehensive educational platform aimed at bridging the Information Technology knowledge gap among Tamil-speaking students in Sri Lanka. The platform is designed to enhance programming skills through personalized quizzes, hands-on projects, and adaptive learning models. The application focuses on two primary components: the first component emphasizes project-based learning and assessments, leveraging advanced Artificial Intelligence models for generating educational content. This model is combined with Retrieval-Augmented Generation, which retrieves relevant external information to refine and tailor the educational content to each student's needs. This component keeps students engaged and challenged at appropriate levels, promoting deeper understanding and practical Information Technology skills. The second component involves a Level-based IT Fundamental Knowledge Evaluation system, which incorporates machine learning algorithms to predict student performance, recommend customized learning paths, and assess overall technical knowledge. The platform also integrates the OpenAI Application Programming Interface, which provides real-time Tamil translation, making the content more accessible to the target demographic. The platform empowers educators to better address individual student needs with real-time feedback and tailored experiences. Its innovative approach enhances Information Technology education, equipping Sri Lankan students with essential programming skills to succeed globally. © 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500页 << < 456 457 458 459 460 461 462 463 464 465 > >>

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：