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

2,381 篇 会议
1,314 篇 期刊文献
37 册 图书

馆藏范围

3,732 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,267 篇 工学
- 1,627 篇 计算机科学与技术...
- 1,340 篇 软件工程
- 618 篇 信息与通信工程
- 360 篇 控制科学与工程
- 302 篇 生物工程
- 283 篇 电气工程
- 229 篇 生物医学工程（可授...
- 215 篇 电子科学与技术（可...
- 180 篇 光学工程
- 159 篇 网络空间安全
- 157 篇 机械工程
- 135 篇 化学工程与技术
- 127 篇 安全科学与工程
- 111 篇 动力工程及工程热...
- 106 篇 交通运输工程
- 104 篇 仪器科学与技术
1,343 篇 理学
- 601 篇 数学
- 475 篇 物理学
- 328 篇 生物学
- 213 篇 统计学（可授理学、...
- 153 篇 化学
- 113 篇 系统科学
690 篇 管理学
- 433 篇 管理科学与工程(可...
- 291 篇 图书情报与档案管...
- 155 篇 工商管理
217 篇 医学
- 159 篇 基础医学(可授医学...
- 158 篇 临床医学
- 109 篇 公共卫生与预防医...
- 94 篇 药学(可授医学、理...
127 篇 法学
- 106 篇 社会学
66 篇 经济学
65 篇 农学
36 篇 教育学
34 篇 文学
20 篇 军事学
5 篇 艺术学
1 篇 哲学

主题

170 篇 accuracy
139 篇 deep learning
102 篇 feature extracti...
100 篇 hadron colliders
97 篇 machine learning
89 篇 computational mo...
89 篇 training
83 篇 convolutional ne...
70 篇 real-time system...
66 篇 support vector m...
63 篇 predictive model...
61 篇 artificial intel...
54 篇 optimization
53 篇 internet of thin...
49 篇 reliability
46 篇 genetic algorith...
45 篇 security
45 篇 cloud computing
45 篇 data models
44 篇 semantics

机构

133 篇 yerevan physics ...
130 篇 national and kap...
130 篇 centro brasileir...
130 篇 istanbul technic...
128 篇 university of sp...
128 篇 indian institute...
127 篇 universidad iber...
126 篇 brunel universit...
125 篇 università di to...
125 篇 academy of scien...
125 篇 charles universi...
125 篇 infn sezione di ...
124 篇 department of ph...
123 篇 zhejiang univers...
123 篇 irfu cea univers...
122 篇 infn sezione di ...
121 篇 university of de...
121 篇 department of ph...
119 篇 imperial college...
119 篇 rwth aachen univ...

作者

125 篇 m. lu
95 篇 g. tonelli
95 篇 d. barney
95 篇 l. valencia palo...
95 篇 t. liu
95 篇 c. hensel
95 篇 a. garcia-bellid...
95 篇 a. steen
95 篇 n. cartiglia
95 篇 d. eliseev
94 篇 a. babaev
94 篇 v. karjavine
93 篇 n. colino
93 篇 f. moortgat
92 篇 b. clerbaux
91 篇 g. sultanov
91 篇 a. mallampalli
91 篇 m. a. ciocci
91 篇 k. lamichhane
91 篇 s. maselli

语言

3,514 篇 英文
173 篇 其他
44 篇 中文
2 篇 日文
1 篇 德文
1 篇 法文

检索条件"机构=Computer Science Engineering and Application"

共 3732 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：

A Novel Procedure for Recognising Human Activity Using Machine Learning 4

A Novel Procedure for Recognising Human Activity Using Machi...

引用

4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Singh, Neelam Bhatt, Mansi Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Department of Computer Application Dehradun India

ISBN: (纸本)9798350300888

In the past few years it is seen that there has been a boom in the usage of smart devices consisting of sophisticated sensors such as gyroscope or gyro and accelerometer. Human Activity Recognition (HAR) is one of these sensors' applications. Given the dependence on general Machine Learning (ML) techniques, Deep learning techniques are suggested by current research to be suitable for feature extraction from unprocessed sensor data. The study focuses on Human Activity Recognition (HAR) by means of data gathered from smartphone accelerometer sensors and employs Long-Short Term Memory (LSTM) networks in the time-series domain. Furthermore, a hybrid network consisting of a 2-layer RNN-LSTM is proposed to enhance the accuracy of recognition performance. For the input and output activation function in the neural network ReLU and Softmax function respectively are used. © 2023 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

A Comparative Analysis of Machine Learning Models for Colon Cancer Classification

A Comparative Analysis of Machine Learning Models for Colon ...

引用

2023 International Conference in Advances in Power, Signal, and Information Technology, APSIT 2023

作者： Swain, Rashmi Ranjan Nayak, Debasish Swapnesh Kumar Swarnkar, Tripti Siksha 'o' Anusandhan University Department of Computer Application Bhubaneswar India Siksha 'o' Anusandhan University Department of Computer Science and Engineering Bhubaneswar India

ISBN: (纸本)9798350339369

One of the trickiest machine learning challenges is the automatic classification of cancer cells. Colon Cancer can strike anyone at any age, but it often strikes older persons. In recent years, several investigations have focused on developing machine learning algorithms that can automatically classify genes of various types of a particular disease, especially colon cancer. The classification of cancer has improved due to improvements in computational methods like machine learning (ML), which required little human interaction and inefficient computers. Since the classification of gene expression data has been extensively studied in conjunction with the advancement of gene technology, a wide variety of techniques, primarily neural network-related, have been applied to the analysis of medical data, which is primarily concerned with the large dimension and very small in quantity. In this work, five different ML techniques were implemented for the classification of colon cancer in different age groups. The implemented ML techniques are Random Forest (RF), Decision Tree (DT), Support vector Machine (SVM), Naive Bayes (NB), and K-Nearest Neighbour (KNN). It is observed that most of the implemented model has an average accuracy of more than 95%. © 2023 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Remotely Controlled Electronic Noticeboard Using NodeMCU 14

Remotely Controlled Electronic Noticeboard Using NodeMCU

引用

14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Kumar, Ayush Singh, Gurpreet Rawat, Vandana Negi, Deepti Joshi, Aditya Graphic Era Deemed to Be University Department of Computer Application Dehradun India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India Graphic Era Hill University Department of Computer Science & Engineering Dehradun India

ISBN: (纸本)9798350335095

In today's digital age, traditional notice boards are being replaced by more dynamic and interactive solutions. This research paper presents the design and implementation of a remotely controlled notice board using the NodeMCU ESP8266 microcontroller and an 8x8 matrix display. The system allows users to remotely update and display messages or notifications in real-time, enhancing communication efficiency and flexibility. By leveraging the capabilities of the NodeMCU ESP8266 and the visual output of the 8x8 matrix display, this solution offers an innovative approach to notice board management. The paper discusses the hardware and software components, the communication protocol, and explores the potential applications of this technology in various settings such as educational institutions, offices, and public spaces. The findings demonstrate the effectiveness and reliability of the proposed solution and emphasize its significance in improving communication processes. This research also highlights potential future enhancements and expansions, paving the way for further advancements in the field of remotely controlled notice boards. © 2023 IEEE.

关键词： Remote control

来源：评论

学校读者我要写书评

暂无评论

Leveraging Machine Learning for Early Detection of Cardiovascular Diseases

Leveraging Machine Learning for Early Detection of Cardiovas...

引用

2025 IEEE International Conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Shrivastava, Anurag Maindola, Meenakshi Kumar, Rakesh Thethi, H. Pal Sreeja, S.P. Sirisha, N. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India GLA University Department of Computer Engineering & Applications Mathura India Lovely Professional University Phagwara India New Horizon College of Engineering Master of Computer Application Bangalore India MLR Institute of Technology Department of Computer Science & Engineering Telangana Hyderabad India

ISBN: (纸本)9798331512965

In order to enhance patient outcomes, rapid and precise detection approaches are needed for cardiovascular diseases (CVDs), which are among the top causes of death globally. By examining a wide range of demographic and clinical data, this study investigates how machine learning approaches could improve the early diagnosis of CVDs. We explore how many different machine learning methods could identify different heart diseases. Decision trees, support vector machines and more, are included in these algorithms. By using feature selection and optimization methods we want to strengthen these models' prediction abilities and make them more resilient. The dataset used by this research includes all of the medical information of patients as they include all the pertinent biomarkers such as age, blood pressure, cholesterol levels and etc. The results suggest that machine learning models, especially ensemble methods like Random Forest and gradient boosting, are indeed able to predict the risk of CVD better than conventional diagnostic strategies. Results suggest that early risk assessment using machine learning embedded within healthcare processes is a reliable and non-invasive approach. This study has found machine learning to have promise for change and further research into the practical use of these models to revolutionize treatment of cardiovascular diseases. © 2025 IEEE.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

Conventional Neural Network for Maths Handwritten Digit Categorization 6

Conventional Neural Network for Maths Handwritten Digit Cate...

引用

6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Garg, Shivya Kuchhal, Navya Barmola, Jigyasa Rawat, Vandana Singh, Neelam Graphic Era Deemed to Be University Department of Computer Application Dehradun India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India

ISBN: (纸本)9798350304480

Handwritten digit recognition plays a crucial role in various sectors such as document processing, automatic form identification, and postal automation. This task involves accurately identifying and classifying handwritten digits into their respective numerical values. This presentation provides a summary of current developments in machine learning techniques for handwritten digit recognition. The primary objective of this research is to develop an advanced system for recognizing handwritten digits by harnessing state-of-the-art machine learning techniques. To train and test the suggested system, a sizable dataset of handwritten digits is used. We are utilizing the MNIST dataset here. To improve the quality of the input pictures and guarantee uniform feature representation, preprocessing techniques like image enhancement and normalization are used. Experimental results indicate that the CNN model surpasses all other investigated techniques in accuracy, boasting an impressive accuracy rate of over 98%. The capacity of the CNN model to automatically deduce pertinent characteristics from the input pictures, catching both local and global patterns, is credited with its better performance. Additionally, the model can successfully handle spatial relationships in the digit pictures because to CNNs'usage of convolutional layers. A number of practical applications, such as computerized form processing, digital document analysis, and intelligent character recognition, are possible with the suggested handwritten digit recognition system. The CNN model's high accuracy enables accurate digit categorization, enhancing efficiency and accuracy across a variety of applications. Future research can concentrate on investigating ensemble approaches, data augmentation methods, and fine-tuning techniques to improve the handwritten digit recognition system's performance even further. © 2023 IEEE.

关键词： CNN digit recognition epochs Handwritten recognition hidden layers machine learning neural network

来源：评论

学校读者我要写书评

暂无评论

Enhanced SMOTE Strategy for Handling Imbalanced Data in Machine Learning Classification

Enhanced SMOTE Strategy for Handling Imbalanced Data in Mach...

引用

2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Tiwari, Shivam Bhardwaj, Barkha Rathore, Yogesh Singh Vats, Satvik Vishwakarma, Pramod Department of Computer Science & Engineering Sharda University Greater Noida India Department of Computer Science and Engineering NIET Greater Noida India Computer Science and Application Sharda University Greater Noida India Computer Science & Engineering Graphic Era Hill University Dehradun India Chandigarh University Gharuan Punjab Mohali India

ISBN: (纸本)9798350305708

Most real-time datasets have class instances scattered across the data in a non-uniform fashion. Certain classes have an abnormally high number of instances when compared to the rest of the classes. The term "class imbalance problem" is used to describe this occurrence (CIP). Due to its inaccuracy in projecting weak class data samples, this skewed information impacts the reliability of forecasts as a whole. Many businesses make use of CIP's data mining experts who employ CIP. Both ML and deep learning have substantial difficulties with the classification of skewed data (DL). Several researchers are curious in how to overcome the major hurdle presented by the widespread adoption of sample techniques to improve classifier performance. In this research, we provide a survey of state-of-the-art approaches currently being used in studies of data classification, and we contrast and compare the numerous algorithms used at each stage of the process. Talk about the challenges and limitations that come up in investigations of imbalanced data classification. Taken as a whole, this work not only provides an in-depth analysis of the uneven data categorization industry but also inspires more study in this space. © 2023 IEEE.

关键词： balanced data classification deep learning each sampling method has a connection to the issue of class imbalance Machine learning

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Study of a Conversational AI-Driven Healthcare Bot with Pose Estimation for Precision Fitness Monitoring and Personalized Guidance

A Comprehensive Study of a Conversational AI-Driven Healthca...

引用

2024 IEEE International Conference on Big Data and Machine Learning, ICBDML 2024

作者： Sinha, Anurag Kumar, Biresh Kundu, Roumo Sharma, Amit Sharma, Mukesh Raza, Asif ICFAI University ICFAI Tech School Computer Science Department Jharkhand Ranchi India Amity University Department of Computer Engineering and Application Jharkhand India Amity Institute of Information Technology Amity University Jharkhand Jharkhand Ranchi India Lovely Professional University Department of Computer Science Phagwara India Amity University Department of Master of Computer Application Jharkhand Ranchi India

ISBN: (纸本)9798350374100

This research investigates a new healthcare paradigm through the analysis of a conversational AI-powered healthcare bot that has posture estimation capabilities for accurate fitness tracking and customized recommendations. User motions during workout routines are accurately and thoroughly assessed thanks to the incorporation of powerful posture estimation technology. With the help of individualized exercise advice, this thorough study explores the capabilities of the system and shows how it may transform wellness practices. The healthcare bot provides an innovative method of fitness tracking by using conversational AI and accurate posture prediction to customize recommendations based on user requirements. This novel combination promises to enhance wellbeing and provide consumers with a more efficient and customized workout experience. The study emphasizes this point. © 2024 IEEE.

关键词： Health care

来源：评论

学校读者我要写书评

暂无评论

Evaluation Of The Efficiency Of Honeypots In Opposing Flooding Attack

Evaluation Of The Efficiency Of Honeypots In Opposing Floodi...

引用

2023 International Conference on Computational Intelligence and Sustainable engineering Solution, CISES 2023

作者： Singh, Neelam Sharma, Deeksha Rawat, Vandana Graphic Era Deemed to Be University Department of Computer Science and Engineering Dehradun India Graphic Era Deemed to Be University Department of Computer Application Dehradun India

ISBN: (纸本)9798350323917

The significance of internet security cannot be overstated for both individuals and organizations, given the increasing threat of malicious cyber-attacks. To enhance internet security, implementing honeypot system is a practical solution. A honeypot is a highly effective security forensic solution that minimizes the possibilities of intrusion and detects potential security vulnerabilities within a system This paper gives a thorough analysis of honeypots and various attack types, and it emphasizes how they may be used to increase the security of a company and its vital network systems. This study uses a pent box honeypot to evaluate the honeypot system's defense against flooding attacks and look at the recorded intrusion attempts. Honeypots, which serve as a line of defense for our networks, have shown to be a successful method of increasing internet security. The study uses the Pent Box tool to deploy honeypots, test them against syn assaults, and analyse the results based on log data. Honeypots can lessen computer network threats and give significant statistics about probable system security holes. © 2023 IEEE.

关键词： Floods

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Survey on Malware Detection Techniques 5

A Comprehensive Survey on Malware Detection Techniques

引用

5th International Conference on Information Management and Machine Intelligence, ICIMMI 2023

作者： Joshi, Yogesh Kumar Tiwari, Nirupma Department of Computer Science Ujjain Engineering College MP Ujjain India Department of Computer Application SAGE University M.P Indore India

ISBN: (纸本)9798400709418

Malware, malicious software designed to infiltrate and compromise computer systems, poses an ever-growing threat in today's interconnected world. This comprehensive review delves into the diverse landscape of malware detection techniques. We categorize and analyze these techniques. Each approach's strengths, weaknesses, and real-world applications are thoroughly examined. Evaluation metrics crucial to assessing detection effectiveness are elucidated. This paper aims to provide a comprehensive overview of the challenges in malware detection techniques face in protecting cyberspace against attacks, by presenting a literature on such emerging techniques for cyber security. It also provides brief descriptions of each techniques method. It finally discusses the challenges of using these techniques in cyber security. This paper provides the latest extensive bibliography and the current trends of malware detection. © 2023 ACM.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

An Enhance Version of YouTube Video Downloader Using Python 1

An Enhance Version of YouTube Video Downloader Using Python

引用

1st International Conference on computer science and Emerging Technologies, CSET 2023

作者： Rawat, Ayush Rawat, Vandana Singh, Neelam Kuchhal, Navya Barmola, Jigyasa Negi, Harendra Singh Graphic Era Deemed to Be University Department of Computer Application Dehradun India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India

ISBN: (纸本)9798350341737

YouTube has become the dominant online video platform, fueling demand for downloading content. In response, numerous third-party tools have emerged to enable downloading YouTube videos, though this violates their terms of service. This research presents the development and evaluation of a custom YouTube video downloader application in Python. The motivation is building an easy-to-use yet customizable solution for saving YouTube videos locally. The tool combines a graphical user interface using PySimpleGUI with the yt-dlp media extraction library. Key innovations include supporting flexible customization of download settings, bulk playlist/channel downloads, a modular architecture, cross-platform packaging, and open source release. Quantitative performance evaluations reveal efficient resource usage, throughput, and scalability when downloading high resolution videos in bulk. User studies highlight satisfaction with the extensive features compared to alternative download tools. However, increased access poses ethical considerations around copyright compliance and fair use versus abuse. While technical and usability goals are largely achieved, fostering responsible use relies on user discretion. Ongoing interdisciplinary research can help guide ethical innovation in this controversial domain. The main contributions are the functional open source tool itself, performance bench marking, user experience evaluations, analysis of legal/ethical impacts, and promotion of community enhancement. © 2023 IEEE.

关键词： Python

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374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：