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

87,590 篇 会议
14,749 篇 期刊文献
688 册 图书
34 篇 科技报告

馆藏范围

103,061 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

66,106 篇 工学
- 46,525 篇 计算机科学与技术...
- 38,644 篇 软件工程
- 16,734 篇 信息与通信工程
- 10,122 篇 控制科学与工程
- 8,793 篇 电气工程
- 8,732 篇 电子科学与技术（可...
- 5,910 篇 生物工程
- 4,756 篇 生物医学工程（可授...
- 4,215 篇 光学工程
- 3,881 篇 机械工程
- 3,314 篇 动力工程及工程热...
- 3,268 篇 仪器科学与技术
- 2,741 篇 化学工程与技术
- 2,059 篇 安全科学与工程
- 1,858 篇 建筑学
- 1,853 篇 材料科学与工程（可...
- 1,836 篇 交通运输工程
34,224 篇 理学
- 20,047 篇 数学
- 9,217 篇 物理学
- 6,544 篇 生物学
- 6,040 篇 统计学（可授理学、...
- 3,946 篇 系统科学
- 2,892 篇 化学
15,988 篇 管理学
- 9,055 篇 管理科学与工程(可...
- 7,730 篇 图书情报与档案管...
- 5,119 篇 工商管理
3,739 篇 医学
- 3,256 篇 临床医学
- 3,055 篇 基础医学(可授医学...
- 1,993 篇 药学(可授医学、理...
2,869 篇 法学
- 2,406 篇 社会学
1,750 篇 经济学
1,459 篇 教育学
1,192 篇 农学
422 篇 文学
258 篇 军事学
112 篇 艺术学
39 篇 哲学
19 篇 历史学

主题

2,246 篇 accuracy
2,154 篇 computational mo...
1,946 篇 feature extracti...
1,892 篇 computer science
1,674 篇 training
1,429 篇 deep learning
1,260 篇 machine learning
1,121 篇 real-time system...
1,089 篇 computer archite...
1,084 篇 predictive model...
1,057 篇 support vector m...
1,042 篇 data mining
985 篇 optimization
906 篇 neural networks
876 篇 semantics
873 篇 data models
787 篇 artificial intel...
768 篇 wireless sensor ...
758 篇 monitoring
753 篇 internet of thin...

机构

112 篇 dept. of electri...
90 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 ...
66 篇 università di ca...
65 篇 dept. of compute...
61 篇 dept. of electr....
57 篇 dept. of electri...
56 篇 dept. of compute...
52 篇 dept. of electri...
52 篇 school of automa...
52 篇 dept. of compute...
44 篇 dept. of compute...
42 篇 infn lnf via enr...
39 篇 dept. of compute...
37 篇 in2p3 lpc campus...
35 篇 dept. of informa...

作者

94 篇 ardid m.
93 篇 ferrara g.
87 篇 calvo d.
80 篇 chen a.
62 篇 ahmad jalal
60 篇 kulikovskiy v.
51 篇 gal t.
42 篇 bozza c.
41 篇 gagliardini s.
40 篇 benoit d.m.
40 篇 eddymaoui a.
39 篇 labalme m.
36 篇 androulakis g.
32 篇 de palma m.
29 篇 sharma neha
28 篇 zhang lei
27 篇 david reigosa
26 篇 kougianos elias
26 篇 marojevic vuk
26 篇 li xin

语言

98,316 篇 英文
3,376 篇 其他
974 篇 中文
262 篇 朝鲜文
118 篇 日文
13 篇 德文
9 篇 土耳其文
7 篇 法文
6 篇 西班牙文
4 篇 斯洛文尼亚文
3 篇 葡萄牙文
2 篇 俄文
1 篇 阿拉伯文

检索条件"机构=Computer Science and Computer Engineering Dept."

共 103061 条记录，以下是311-320 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 Mobile Application for the Crowdsensing of Road Pavements Conditions 22

A Mobile Application for the Crowdsensing of Road Pavements ...

引用

22nd IEEE Consumer Communications and Networking Conference, CCNC 2025

作者： Delnevo, Giovanni Bartolucci, Nicola Mirri, Silvia Salomoni, Paola Prandi, Catia University of Bologna Dept. of Computer Science and Engineering Italy University of Bologna Bachelor Degree in Computer Science and Engineering Italy

ISBN: (纸本)9798331508050

Urban environments face significant challenges due to deteriorating road pavements, affecting all transportation modes' safety and comfort. Traditional methods of road assessment are costly and infrequent, but advancements in mobile technology and crowdsensing offer real-time, large-scale data collection solutions. This paper introduces 'ShakeSensing', a mobile application that uses Android device sensors to measure vibrations experienced by cyclists and scooter users, providing insights into road quality. The collected data, analyzed to assess road conditions, can benefit both users and municipal authorities, promoting safer and more comfortable travel. © 2025 IEEE.

关键词： Urban transportation

来源：评论

学校读者我要写书评

暂无评论

Fabric Defect Detection using Deep Learning 3

Fabric Defect Detection using Deep Learning

引用

3rd International Conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Kailasam, Khushi Singh, Jaswant Gopika, G.S. Sreekrishna, M. Supriya, S. Sathyabama Institute of Science and Technology Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350396157

Fabric defect detection plays a crucial role in the textile manufacturing industry's quality control process since it guarantees that customers will receive perfect products. Deep Learning (DL) models have demonstrated a great deal of promise in recent years for accurately identifying fabric defects. The proposed fabric defect identification method combines the best features of two architectures: You Only Look Once (YOLOv4) and Region-based Convolutional Neural Network (R-CNN). While YOLOv4 offers quicker and more effective detection, R-CNN generates region recommendations that allow accurate localization of fabric defects. There are two stages in the proposed system. Initially, region proposals are detected using the R-CNN feature extractor and then a convolutional neural network is used for defect classification. YOLOv4 is used for performing object detection in the second step, where the flaws are concurrently classified and localized. The tests carried out on a fabric defect dataset show that the proposed method outperforms the R-CNN and YOLOv4 models separately. The proposed system is appropriate for real-Time fabric flaw detection applications in a variety of sectors due to its high detection accuracy and quick processing time. This study demonstrates how well R-CNN and YOLOv4 together work for fabric flaw detection, providing hope for future developments in the area. © 2024 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Model for Weather Prediction 1

Deep Learning Model for Weather Prediction

引用

1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Singh, Shubhanshi Tyagi, Neha Amity School of Engineering and Technology Dept. Computer Science and Engineering Noida India

ISBN: (纸本)9798350353648

Weather forecasting predicts atmospheric conditions at a particular time and place. It is an important task with a wide range of applications, including agriculture, transportation, and disaster prevention. Traditional weather forecasting methods rely on physical models of the atmosphere, which can be complex and computationally expensive. In recent years, deep learning techniques are effective for weather forecasting. Deep learning models can learn complex patterns from data, which can be used to predict future weather conditions accurately. This project aims to create a deep-learning model for forecasting weather. A huge dataset of historical meteorological data, including radar, satellite, and surface measurements, will be used to train the model. Numerous meteorological factors, such as temperature, precipitation, and wind speed, will be predicted by the model. We will compare the deep learning model's performance with conventional weather forecasting techniques. Creating a deep learning model that is more accurate and effective than current approaches is the project's main objective. The initiative may result in improved weather forecasts that are prompt and accurate, better agricultural, transportation, and disaster prevention decision-making, and less money lost because of weather-related incidents. Possible obstacles for the project are gathering and purifying a sizable dataset of meteorological data, using this data to train a deep learning model, and then comparing the model's output with more conventional techniques. © 2024 IEEE.

关键词： Wind forecasting

来源：评论

学校读者我要写书评

暂无评论

Smart Gadgets Cockpit Using IoT 1

Smart Gadgets Cockpit Using IoT

引用

1st IEEE International Conference on Computing and Data science, ICCDS 2024

作者： Eapen, Maya Mercy, H. Beulah Jayakumari, R. Lavanya Mala, A. Indumathi, S. Pooja, S. Jerusalem College oif Engineering Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350365337

The Smart Device Cockpit collects data from IoT enabled household appliances like Air conditioner, refrigerators, microwave ovens, and washing machines. Once transmitted to the Smart Device Cockpit portal, the data undergoes analysis and is then presented in the form of both usage data and error data. This platform facilitates a thorough comprehension of the utilization patterns of these household devices and offers insights into any possible errors or malfunctions that may occur. In essence, the Smart Device Cockpit serves as a powerful tool for homeowners to not only monitor and manage their smart appliances but also to make informed decisions about usage optimization and timely maintenance. © 2024 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

A Fusion-Based Approach to Multiclass Retinal Disease Classification: Transfer Learning Strategy with CBAM Integration 2

A Fusion-Based Approach to Multiclass Retinal Disease Classi...

引用

2nd International Conference on Power, Electrical, Electronics and Industrial Applications, PEEIACON 2024

作者： Nath, Bijoy Deb Afroge, Shyla Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi Bangladesh

ISBN: (纸本)9798331517984

Eye diseases pose significant global public health challenges, often resulting to irreversible blindness if untreated. Early, precise diagnosis of these disorders is critical. In this paper, we address this crucial issue using transfer learning methods for the categorization of multiple eye disorders. The proposed architecture features a fusion-based technique that combines EfficientNetB0 and MobileNetV3Large convolutional neural networks (CNNs) for feature extraction and incorporates Convolutional Block Attention Module (CBAM), which dynamically focuses on significant regions of the images, enhancing the model's discriminative capability. Our proposed model achieves outstanding performance on two separate datasets: 97.85% accuracy on the Eye Disease Classification (EDC) dataset and 91.96% on the Ocular Disease Intelligent Recognition (ODIR) dataset, surpassing existing state-of-the-art approaches in ocular disease classification. By developing the proposed model, we intend to contribute to the creation of more effective diagnostic tools and eventually enhance patient outcomes in ophthalmology. © 2024 IEEE.

关键词： Ophthalmology

来源：评论

学校读者我要写书评

暂无评论

Unravel News: An Efficient Summarization Approach

Unravel News: An Efficient Summarization Approach

引用

2024 IEEE International Conference on Computing, Applications and Systems, COMPAS 2024

作者： Saha, Ankan Al Shafi, Abdullah Khulna University of Engineering and Technology Dept. Computer Science and Engineering Khulna Bangladesh

ISBN: (纸本)9798331529765

The process of automatically creating a concise and informative summary of a news piece is known as news summarizing. This can be a useful tool for people who want to quickly get the gist of a news story without having to read the entire article. Extractive and abstractive summarization are the two basic methods used to summarize news. The process of extractive summarization entails locating and separating the key phrases from the source text. In this paper, sentence weighting is used for extractive summarization. The words in the headlines are given ten times more emphasis than the other words in the news article. The final summarization is done by rearranging the sentences as per the sequence in the main news article. The paper concludes by discussing the future of news summarization, which is an active area of research. © 2024 IEEE.

关键词： Abstractive Summary Extractive Summary ROUGE Sentence Rank Algorithm Stemming Text Rank Algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimizing Job Search: A Multi-Model Approach with DRNN-BES, Collaborative Filtering, and LLM-NER Resume Analysis 3

Optimizing Job Search: A Multi-Model Approach with DRNN-BES,...

引用

3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Jayakumar, Naveenkumar Patil, Netra Pokal, Roshankumar S. Dev, Rudra Pratap Nair, Sidharth Vellore Institute of Technology School of Computer Science and Engineering Vellore India College of Engineering Dept. of Computer Engineering Pune India

ISBN: (纸本)9798350354348

This research introduces an innovative job recommendation platform designed to optimize the job search process through advanced technology integration. The platform features a sophisticated Resume Analyzer leveraging NLP and ML to meticulously extract candidate information. Coupled with a Recommendation System that employs mixture models such as DRNN-BES and collaborative filtering, it delivers personalized job suggestions tailored to individual profiles. Additionally, the system utilizes state-of-the-art web scraping technologies to continuously update its database with diverse and current job listings from various online sources, ensuring a wide range of opportunities are accessible. This integration of technologies not only refines job-matching precision but also significantly improves the efficiency of connecting job seekers with appropriate opportunities. Initial experimental results underscore the enhanced effectiveness and accuracy of our recommendation system, particularly when incorporating user behavioral data into the collaborative filtering algorithm. This paper demonstrates the transformative potential of integrating AI into job seeking, offering a scalable, unbiased, and time-efficient approach to modern employment challenges. © 2024 IEEE.

关键词： Collaborative filtering

来源：评论

学校读者我要写书评

暂无评论

A web-based biometric system for e-voting

A web-based biometric system for e-voting

引用

2024 International Conference on science, engineering and Business for Driving Sustainable Development Goals, SEB4SDG 2024

作者： Abiodun, Moses Kazeem Adeniyi, Jide Kehinde Adeniyi, Abidemi Emmanuel Awotunde, Joseph Bamidele Aremu, Dayo Rueben Samuel, Olabode Adebiyi, Ayodele A Atanda, Oladayo G. Landmark University Dept. of Computer Science Omu-Aran Nigeria Bowen University Dept. of Computer Science Iwo Nigeria University of Ilorin Dept. of Computer Science Ilorin Nigeria

ISBN: (纸本)9798350358155

Voting is an important activity, and it is an inevitable event in our everyday life. Voting has been conducted in various ways some of which are the use of ballot papers or raising of hands and further collating its statistics manually. The election process in Nigeria has a lot of vulnerabilities, ranging from when the users are casting their votes manually to when the votes are being counted by officials. In previous years Nigerian elections has had a lot of controversy concerning its accuracy and *** major reason for this research is to reduce the rate of corruption in voting and further make it easier for citizens of Nigeria to cast their votes. An electronic voting system is proposed that make use of two-level authentication system, the National Identification Number (NiN) and the facial recognition of voters. The system was implemented using technologies like HTML (Hypertext Markup Language), CSS (Cascade Styling Sheet), JS (JavaScript) language used for the client-side and node JS (JavaScript) used on the server-side. Mongo DB was used as the *** results of evaluation of the system are very encouraging, 87.7% of the respondent attest to how the integration of the application and its functionality. There was a positive respond for determining the speed of page transition. 87.7% says the loading time of the web application is very *** on the evaluation of this system and its performance, the e-voting system is therefore recommended to be used in Nigeria for next election. © 2024 IEEE.

关键词： Markup languages

来源：评论

学校读者我要写书评

暂无评论

Image Segmentation based Approach for Skin Disease Detection and Classification using Machine Learning Algorithms 2

Image Segmentation based Approach for Skin Disease Detection...

引用

2nd IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2024

作者： Sany, Nazmul Hasan Chandra Shill, Pintu Khulna University of Engineering & Technology Dept. of Computer Science and Engineering Khulna Bangladesh

ISBN: (纸本)9798350317558

Skin disorders are ubiquitous, stemming from causes including fungus, germs, allergies, and viruses. Although laser and photonics medical technologies have revolutionised rapid and precise diagnosis, their exorbitant prices restrict accessibility. To address this, this paper describes an image processing strategy for dermatological screening and procedure that comprises obtaining digital photographs of damaged skin patches and applying image processing to detect the disease type. Moreover, when conducted manually by medical specialists, identifying skin illnesses is time-intensive and subjective. As a consequence, both patients and physicians want automated skin disease prediction, which makes the treatment plan faster. This cost-effective approach depends on a basic setup: a camera and a computer. Operating on colour photos, a solution combines resizing for feature extraction using a pertained convolutional neural network, followed by classification using a multiclass SVM. The technology efficiently recognises four separate skin illnesses with an astonishing 90.8% accuracy, giving users complete findings spanning disease kind, extent, and severity. © 2024 IEEE.

关键词： Decision Tree Image Processing K-NN Machine Learning Skin Disorder SVM

来源：评论

学校读者我要写书评

暂无评论

Deepfake Detection Using Multi-Modal Fusion Combined with Attention Mechanism 4

Deepfake Detection Using Multi-Modal Fusion Combined with At...

引用

4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Shirley, C.P. Berin Jeba Jingle, I. Abisha, M.B. Venkatesan, R. Yashvanth Ram, R.V. Elango, Elakkiya Karunya Institute of Technology and Sciences Dept. of Computer Science and Engineering Coimbatore India Government Arts College for Woman Dept. of computer Science Sivaganga India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540364

The proliferation of deepfake technology poses a significant challenge to the authenticity of digital content. This research explores the application of multimodal fusion techniques to enhance deepfake detection accuracy. By combining visual and audio features, the proposed method leverages the complementary nature of different data types to detect discrepancies introduced by deepfake manipulation. An attention mechanism is incorporated to focus on salient regions within each modality, further improving detection accuracy. Convolutional Neural Networks (CNNs) and Mel-Frequency Cepstral Coefficients (MFCCs) are employed for feature extraction, followed by feature fusion for deepfake detection. This approach demonstrates the effectiveness of multimodal fusion in combating the evolving threat of deepfake technology. By advancing deepfake detection techniques, this research contributes to safeguarding the integrity of digital content and preserving trust in media. © 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

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 << < 28 29 30 31 32 33 34 35 36 37 > >>

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：