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

5,626 篇 会议
90 篇 期刊文献
10 册 图书

馆藏范围

5,726 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,768 篇 工学
- 2,326 篇 计算机科学与技术...
- 1,324 篇 软件工程
- 566 篇 信息与通信工程
- 466 篇 电气工程
- 200 篇 生物工程
- 176 篇 控制科学与工程
- 174 篇 生物医学工程（可授...
- 109 篇 机械工程
- 84 篇 交通运输工程
- 83 篇 化学工程与技术
- 81 篇 电子科学与技术（可...
- 79 篇 光学工程
- 70 篇 仪器科学与技术
- 65 篇 动力工程及工程热...
- 55 篇 安全科学与工程
- 54 篇 土木工程
- 52 篇 环境科学与工程（可...
899 篇 理学
- 478 篇 数学
- 235 篇 生物学
- 232 篇 物理学
- 191 篇 统计学（可授理学、...
- 119 篇 系统科学
- 67 篇 化学
589 篇 管理学
- 326 篇 图书情报与档案管...
- 307 篇 管理科学与工程(可...
- 164 篇 工商管理
290 篇 医学
- 244 篇 临床医学
- 144 篇 基础医学(可授医学...
- 80 篇 药学(可授医学、理...
76 篇 法学
- 71 篇 社会学
55 篇 经济学
45 篇 教育学
40 篇 农学
26 篇 文学
2 篇 军事学
1 篇 历史学
1 篇 艺术学

主题

1,599 篇 data models
534 篇 predictive model...
529 篇 training
498 篇 machine learning
461 篇 data mining
416 篇 big data
404 篇 computational mo...
343 篇 feature extracti...
333 篇 task analysis
326 篇 prediction algor...
267 篇 deep learning
255 篇 machine learning...
245 篇 classification a...
238 篇 analytical model...
191 篇 clustering algor...
190 篇 support vector m...
182 篇 neural networks
158 篇 natural language...
142 篇 training data
141 篇 mathematical mod...

机构

19 篇 sun yat sen univ...
19 篇 daffodil interna...
12 篇 univ chinese aca...
11 篇 tsinghua univers...
11 篇 university of ch...
11 篇 school of data a...
10 篇 carnegie mellon ...
9 篇 renmin univ chin...
9 篇 lviv polytechnic...
8 篇 shenzhen researc...
7 篇 shanghai jiao to...
7 篇 college of compu...
7 篇 university of el...
7 篇 school of comput...
7 篇 national univers...
7 篇 harbin institute...
7 篇 beijing key lab ...
7 篇 natl univ def te...
7 篇 renmin univ chin...
6 篇 university of sc...

作者

7 篇 li li
7 篇 wang wei
7 篇 xiao yanghua
6 篇 wen ji-rong
6 篇 cui bin
6 篇 zhao wayne xin
6 篇 ying liu
6 篇 syed akhter hoss...
5 篇 yang tong
5 篇 liu yang
5 篇 li zhang
5 篇 jia weijia
5 篇 chen liu
5 篇 yang yang
5 篇 xiao hongbo
5 篇 nguyen trong-the
5 篇 yu jie
5 篇 albert bifet
5 篇 wang bin
5 篇 carlos ordonez

语言

5,682 篇 英文
36 篇 其他
9 篇 中文
2 篇 俄文
1 篇 乌克兰文

检索条件"任意字段=2020 International Conference on Data Processing Algorithms and Models, ICDPAM 2020"

共 5726 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：

Adaptive Fuzzy Level Set Streamflow Modeling and Forecasting 20th

Adaptive Fuzzy Level Set Streamflow Modeling and Forecasting

引用

20th international conference on Information processing and Management of Uncertainty in Knowledge-Based Systems

作者： Maciel, Leandro Ballini, Rosangela Gomide, Fernando Univ Sao Paulo Sch Econ Business Accounting & Actuary Sao Paulo Brazil Univ Estadual Campinas Inst Econ Campinas Brazil Univ Estadual Campinas Sch Elect & Comp Engn Campinas Brazil

ISBN: (纸本)9783031739965;9783031739972

The paper addresses the use of an adaptive, recursive fuzzy modeling based on the notion of level set to forecast monthly streamflows of a major hydroelectric power plant reservoir at the northeast of Brazil. Streamflows are highly complex nonstationary time series with high variability during the year, a feature that turns modeling and forecasting very hard and challenging. The adaptive level set method is evaluated against periodic autoregressive moving average models, currently adopted by many power industries, and against granular, neural, neural fuzzy, recurrent neural, and data driven level set models. The results show that adaptive level set modeling achieves the best root mean square error performance, surpassing all the models considered herein.

关键词： Adaptive fuzzy systems data driven level set modeling Time series forecasting

来源：评论

学校读者我要写书评

暂无评论

Designing and Executing a Large-scale Real-life Affective Study

Designing and Executing a Large-scale Real-life Affective St...

引用

IEEE international conference on Pervasive Computing and Communications (PerCom)

作者： Komoszynska, Joanna Kunc, Dominika Perz, Bartosz Hebko, Adam Kazienko, Przemyslaw Saganowski, Stanislaw Wroclaw Univ Sci & Technol Dept Artificial Intelligence Wroclaw Poland

ISBN: (纸本)9798350304367;9798350304374

Despite advancements in emotion recognition, the suitability of existing AI models for daily use remains uncertain. Creating more accurate solutions requires amounts of data uncollectible in a laboratory setting, thus forcing researchers to focus on a more information-rich environment - everyday life. However, the constraints of the in-the-field studies are different than those of the in-the-lab ones, which are familiar to most researchers. In this work, we delve into the challenges in designing and conducting a large-scale real-life affective study, employing wearable devices and smartphones for data collection. Among others, we describe in detail the impact of delays on the whole process and related issues, such as using untested features and oversights in the main study. Moreover, we highlight other faced challenges, made decisions, and mistakes, which, we believe, are valuable for researchers aiming to conduct studies in a reallife setting.

关键词： real-life study study design emotionally annotated physiology wearables Emognition system affective data collection

来源：评论

学校读者我要写书评

暂无评论

data Quality as a Service Framework for AI-Enabled Industrial Internet of Things 24

Data Quality as a Service Framework for AI-Enabled Industria...

引用

14th international conference on the Internet of Things, IoT 2024

作者： Goknil, Arda Nguyen, Phu Husom, Erik Johannes Sen, Sagar Tverdal, Simeon Peysson, Flavien Politaki, Dimitra González-Velázquez, Roberto SINTEF Oslo Norway PREDICT Nancy France IRT SystemX Paris France TEKNIKER Eibar Spain

ISBN: (纸本)9798400712852

In the era of the Industrial Internet of Things (IIoT), the integration of Artificial Intelligence (AI) and Machine Learning (ML) into industrial processes has significantly enhanced operational efficiency and decision-making capabilities. However, the effectiveness of AI-enabled IIoT systems heavily depends on the quality of the underlying data. Ensuring data integrity, accuracy, and reliability in IIoT is challenging due to the heterogeneous nature of data sources and the dynamic operational conditions. Existing approaches often focus on individual data quality techniques, lacking a unified and comprehensive framework. To address this need, we propose data Quality as a Service (DQaaS), a novel framework designed to provide scalable and reusable data quality solutions as services for AI-enabled IIoT applications. DQaaS encompasses a suite of modular services for data monitoring and repair, all orchestrated through a centralized platform. This framework leverages advanced ML algorithms and state-of-the-art processing techniques to ensure robust data quality management across the edge-cloud continuum. © 2024 Copyright held by the owner/author(s).

关键词： data quality

来源：评论

学校读者我要写书评

暂无评论

Fuzzy c-Means as a Decision Support Tool for Liver Disease Diagnosis Based on data Analysis 4th

Fuzzy c-Means as a Decision Support Tool for Liver Disease D...

引用

4th international conference on Optimization Learning algorithms and Applications

作者： Leite, Gabriel A. Azevedo, Beatriz Flamia Ferreira, Sofia Ribeiro Pacheco, Maria F. Fernandes, Florbela P. Pereira, Ana I. Inst Politecn Braganca Res Ctr Digitalizat & Intelligent Robot CeDRI Lab Associado Sustentabilidade & Tecnol Regioes M P-5300252 Braganca Portugal Unidade Transplante Hepat & Pancreat Porto Portugal Unidade Local Saude Santo Antonio Porto Portugal

ISBN: (纸本)9783031774256;9783031774263

The liver is a vital organ responsible for numerous essential functions in the body. Thus, liver disorders can have severe consequences on overall health and well-being. Early diagnosis and treatment of liver disorders are crucial to prevent complications such as cirrhosis, liver failure and liver cancer. In this work, a data analysis system aims to identify the most important features in defining liver disease and categorize sick patients according to the severity of the disease. The Indian Liver Patient dataset was evaluated using a pre-processing data analysis method that considered the Z-score, the correlation, and the Recursive Feature Elimination. After identifying the most important characteristics of the patients, the Fuzzy c-means algorithm was used to classify them based on the severity of the disease. The results of the proposed methodology proved to be effective in creating a decision support system, since it was possible to identify four levels of severity among the patients.

关键词： Decision support Machine learning Fuzzy clustering

来源：评论

学校读者我要写书评

暂无评论

data Democratisation with Deep Learning: The Anatomy of a Natural Language data Interface 23

Data Democratisation with Deep Learning: The Anatomy of a Na...

引用

16th international conference on Web Search and data Mining

作者： Katsogiannis-Meimarakis, George Xydas, Mike Koutrika, Georgia Athena Res Ctr Athens Greece

ISBN: (纸本)9781450394079

In the age of the Digital Revolution, almost all human activities, from industrial and business operations to medical and academic research, are reliant on the constant integration and utilisation of ever-increasing volumes of data. However, the explosive volume and complexity of data makes data querying and exploration challenging even for experts, and makes the need to democratise the access to data, even for non-technical users, all the more evident. It is time to lift all technical barriers, by empowering users to access relational databases through conversation. We consider 3 main research areas that a natural language data interface is based on: Text-to-SQL, SQL-to-Text, and data-to-Text. The purpose of this tutorial is a deep dive into these areas, covering state-of-the-art techniques and models, and explaining how the progress in the deep learning field has led to impressive advancements. We will present benchmarks that sparked research and competition, and discuss open problems and research opportunities with one of the most important challenges being the integration of these 3 research areas into one conversational system.

关键词： data Democratisation Text-to-SQL SQL-to-Text data-to-Text Deep Learning Natural Language processing

来源：评论

学校读者我要写书评

暂无评论

Forensics Analysis of Residual Noise Texture in digital Images for Detection of Deepfake

Forensics Analysis of Residual Noise Texture in digital Imag...

引用

2025 IEEE international conference on Acoustics, Speech, and Signal processing, ICASSP 2025

作者： Méreur, Arthur Mallet, Antoine Cogranne, Rémi Kuribayashi, Minoru Troyes University of Technology France Center for Data-driven Science and Artificial Intelligence Tohoku University Japan

ISBN: (纸本)9798350368741

This paper proposes an original approach for the automatic detection of AI-generated images, using features derived from noise residuals artefacts. Contrary to most current research that leverages sophisticated deep learning models to further improve performance, this study highlights the distinct noise residual characteristics in deepfakes, facilitating the identification of AI-generative images. Our findings highlight some limitations of image models, which can be used for forensic analysis and for future AI-based text-to-image generative models. Broad numerical results on a large and diverse dataset show the interest of the identified features as well as the relevance of the present method. © 2025 IEEE.

关键词： DeepFakes Explainable method Machine learning Noise residual Statistical detection

来源：评论

学校读者我要写书评

暂无评论

Exploiting the Potential Anomaly Detection in Automobile Safety data with Multi-type Neural Network 20th

Exploiting the Potential Anomaly Detection in Automobile Saf...

引用

20th EAI international conference on Mobile and Ubiquitous Systems - Computing Networking and Services (EAI MobiQuitous)

作者： Guan, Quanlong Zhang, Tian Huang, Xiujie Zhong, Yuansheng Du, Cuifeng Liu, Changjiang Li, Zhefu Zhang, Guanghui Wu, Xiaofeng Duan, Zhifei Jinan Univ Jinan 510632 Guangdong Peoples R China Guangdong Testing Inst Prod Qual Supervis Key Lab Safety Intelligent Robots State Market Re Guangzhou Peoples R China Guangdong Key Lab Data Secur & Privacy Preserving Jinan Guangdong Peoples R China Cetc Potevio Sci & Technol Co Ltd Jinan Guangdong Peoples R China Guangzhou Polytech Sports Guangzhou Peoples R China Guangdong Macao Adv Intelligent Comp Joint Lab Jinan Peoples R China Guangzhou XPeng Motors Technol Co Ltd Jinan Guangdong Peoples R China

ISBN: (纸本)9783031639883;9783031639890

As an internal network widely used in automobiles, the automotive CAN bus network lacks effective security protection mechanisms and is vulnerable to network hackers, posing a serious threat to the safety of vehicles and drivers. The automotive intrusion detection system provides effective protection for the security of the automotive CAN network. To address the shortcomings of current intrusion detection algorithms, such as long application time and incomplete detection types, GIDPS and TIDPS models are proposed to perform supervised multi-classification experiments on vehicle intrusion data. Then, the above model is migrated to the ROAD dataset for verification, and the advantages of the new model in terms of time and accuracy compared with the old model are analysed based on the results. The proposed GIDPS and TIDPS models achieve better results than previous models in terms of synthesis. The new models provides a certain reference value for improving the level of automotive network security. They could be applied to domestic or cross-border automotive markets.

关键词： CAN bus network Intrusion detection Network hackers Multi-classification

来源：评论

学校读者我要写书评

暂无评论

AI data Analytics for Air Quality Modeling 6

AI Data Analytics for Air Quality Modeling

引用

6th international conference on Electrical Engineering and Information and Communication Technology, ICEEICT 2024

作者： Barua, Annandip Babu, Md Abu Ahammed Cox's Bazar International University Department of Computer Science & Engineering Bangladesh Volvo Car Corporation Sweden

ISBN: (纸本)9798350385779

Air quality is a critical concern globally, with implications for public health and environmental sustainability. While improvements have been made since the implementation of the Clean Air Act of 1970, the adverse effects of air pollution persist, leading to significant health burdens and mortality rates worldwide. In this context, this study focuses on analyzing air quality in Leeds, UK, during the year 2020, leveraging data from monitoring stations administered by the Department for Environment, Food, and Rural Affairs (DEFRA). Given the unique circumstances of 2020, which included lockdowns due to the COVID-19 pandemic, this period offers valuable insights into the interplay between human activity and air pollution. The research employs a multi-phase approach, encompassing descriptive, inferential, machine learning, and deep learning analyses to comprehensively understand air quality patterns and predict pollutant concentrations. While existing literature predominantly focuses on other regions, particularly China and India, this study addresses the scarcity of research specific to the UK context. Findings reveal variations in pollutant levels, with particulate matter (PM10 and PM2.5), nitrogen oxides (NO2 and NO) and carbon monoxide (CO) being the primary pollutants of concern. Inferential analyses highlight significant differences in pollutant levels and correlations, potentially influenced by lock-down measures. Machine learning algorithms, notably random forests, demonstrate efficacy in predicting PM2.5 concentrations, mirroring findings from deep learning approaches. However, the study underscores the need for larger and more diverse datasets to enhance predictive accuracy and generalize findings. Future research directions include exploring hybrid deep learning algorithms, refining machine learning models, and expanding data collection efforts across various locations and time periods to better understand the dynamics of air quality. Overall, this research

关键词： Air quality

来源：评论

学校读者我要写书评

暂无评论

Destruction-Restoration Suppresses data Protection Perturbations against Diffusion models 35

Destruction-Restoration Suppresses Data Protection Perturbat...

引用

35th IEEE international conference on Tools with Artificial Intelligence (ICTAI)

作者： Qin, Tianrui Gao, Xitong Zhao, Juanjuan Ye, Kejiang Univ Chinese Acad Sci Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China

ISBN: (纸本)9798350342734

Diffusion models have become popular in computer vision applications due to their ability to generate high-quality images quickly, with some models achieving a high degree of realism. However, the use of these models for novel image manipulation and generation poses significant risks of being used for harmful purposes, such as the spread of misinformation or copyright infringement. Recent research has proposed techniques that involve adding imperceptible perturbations to images to mitigate privacy and copyright concerns. However, trivial image processing methods can largely destroy these protective perturbations. In this paper, we propose a new method called DiffCleaner, a destruction-restoration pipeline, that combines the advantages of image corruption and restoration methods. It can not only remove protective perturbations but also further preserve high quality generation, as well as fidelity of the original features in generated images. DiffCleaner produces specialized images with visualization and quantitative metrics closely matching unprotected results. We pitch a range of circumventing methods vs. two state-of-the-art data protection methods against diffusion models, and show that both are fragile and offer inadequate data protection. By providing a benchmark comprising a range of protective perturbations removal methods, we hope this paper will inspire and facilitate new research towards developing more resilient methods for data protection.

关键词： data privacy data protection Diffusion model Adversarial examples

来源：评论

学校读者我要写书评

暂无评论

Failure Prediction Using Multimodal Classification of PCB Images 13

Failure Prediction Using Multimodal Classification of PCB Im...

引用

13th international conference on data Science, Technology and Applications, data 2024

作者： Goncalves, Pedro M. Brito, Miguel A. Moreira, Jose Guilherme Cruz Bosch Car Multimedia Portugal S.A Braga Portugal Centro Algoritmi University of Minho Braga Portugal

ISBN: (纸本)9789897587078

In the era of Industry 4.0, where digital technologies revolutionize manufacturing, a wealth of data drive optimization efforts. Despite the opportunities, managing these vast datasets poses significant challenges. Printed Circuit Boards (PCBs) are pivotal in modern industry, yet their complex manufacturing process demands robust fault detection mechanisms to ensure quality and safety. Traditional classification models have limitations, exacerbated by imbalanced datasets and the sheer volume of data. Addressing these challenges, our research pioneers a multimodal classification approach, integrating PCB images and structured data to enhance fault prediction. Leveraging diverse data modalities, our methodology promises superior accuracy with reduced data requirements. Crucially, this work is conducted in collaboration with Bosch Car Multimedia, ensuring its relevance to industry needs. Our goals encompass crafting sophisticated models, curbing production costs, and establishing efficient data pipelines for real-time processing. This research marks a pivotal step towards efficient fault prediction in PCB manufacturing within the Industry 4.0 framework. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： data accuracy

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 << < 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：