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

3,117 篇 会议
141 册 图书
24 篇 期刊文献

馆藏范围

3,281 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,141 篇 工学
- 1,954 篇 计算机科学与技术...
- 1,095 篇 软件工程
- 405 篇 信息与通信工程
- 287 篇 电气工程
- 267 篇 生物工程
- 217 篇 控制科学与工程
- 172 篇 生物医学工程（可授...
- 79 篇 化学工程与技术
- 73 篇 光学工程
- 72 篇 机械工程
- 68 篇 仪器科学与技术
- 65 篇 电子科学与技术（可...
- 62 篇 安全科学与工程
- 55 篇 动力工程及工程热...
- 54 篇 网络空间安全
777 篇 理学
- 430 篇 数学
- 296 篇 生物学
- 151 篇 统计学（可授理学、...
- 147 篇 物理学
- 127 篇 系统科学
- 90 篇 化学
505 篇 管理学
- 306 篇 图书情报与档案管...
- 231 篇 管理科学与工程(可...
- 95 篇 工商管理
218 篇 医学
- 193 篇 临床医学
- 125 篇 基础医学(可授医学...
- 87 篇 药学(可授医学、理...
- 55 篇 公共卫生与预防医...
72 篇 法学
- 70 篇 社会学
52 篇 教育学
- 47 篇 教育学
35 篇 经济学
31 篇 农学
6 篇 艺术学
4 篇 军事学
1 篇 文学

主题

568 篇 data mining
542 篇 machine learning
241 篇 pattern recognit...
195 篇 deep learning
174 篇 feature extracti...
154 篇 artificial intel...
153 篇 support vector m...
113 篇 accuracy
113 篇 machine learning...
111 篇 training
93 篇 data models
80 篇 neural networks
77 篇 data mining and ...
65 篇 classification
62 篇 sentiment analys...
61 篇 classification a...
59 篇 big data
57 篇 predictive model...
50 篇 face recognition
48 篇 prediction algor...

机构

7 篇 maharishi school...
6 篇 guangdong univer...
5 篇 galgotias univer...
5 篇 centre of interd...
5 篇 pune
5 篇 chitkara univers...
5 篇 uttaranchal univ...
5 篇 uttaranchal inst...
5 篇 institute of aut...
4 篇 shanghai jiao to...
4 篇 chitkara univers...
4 篇 school of inform...
4 篇 indian statistic...
4 篇 south china univ...
4 篇 zhejiang univers...
4 篇 maharishi school...
4 篇 department of cs...
4 篇 university of ca...
4 篇 school of comput...
4 篇 department of co...

作者

9 篇 de-shuang huang
7 篇 coenen frans
7 篇 venkatesh svetha
7 篇 petra perner
7 篇 tianrui li
6 篇 ryszard tadeusie...
6 篇 marcin korytkows...
6 篇 jacek m. zurada
6 篇 krasotkina olga
6 篇 lotfi a. zadeh
6 篇 mottl vadim
6 篇 leszek rutkowski
5 篇 vitoantonio bevi...
5 篇 sankar k. pal
4 篇 waiyamai kitsana
4 篇 sozo inoue
4 篇 sergei o. kuznet...
4 篇 duoqian miao
4 篇 shengli xie
4 篇 hepu deng

语言

3,063 篇 英文
209 篇 其他
38 篇 中文
1 篇 西班牙文
1 篇 土耳其文

检索条件"任意字段=3rd International Conference on Machine Learning and Data Mining in Pattern Recognition"

共 3282 条记录，以下是661-670 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：

Research on User Demand mining and Repurchase Behavior Prediction Algorithm Selection Based on Big data

Research on User Demand Mining and Repurchase Behavior Predi...

引用

Electrical Engineering, Big data and Algorithms (EEBDA), IEEE international conference on

作者： Tingwei Zhou Shanghai University Shanghai China

Based on the text data of authoritative skin care community, this study analyzes the user's needs and summarizes six topics on the premise that it has the option of repurchase intention. We need to calculate the emotional scores of six topics of each text data and contact the repurchase intention, thus constructing a feature data set, and then exploring which machine learning method is used to predict the repurchase behavior of online community review texts, which is relatively more accurate and reliable.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Passing Heatmap Prediction Based on Transformer Model Using Tracking data for Football Analytics 3rd

Passing Heatmap Prediction Based on Transformer Model Using...

引用

3rd international conference on Intelligent Systems and pattern recognition, ISPR 2023

作者： Pei, Yisheng De Silva, Varuna Caine, Mike Institute for Digital Technologies Loughborough University London London United Kingdom University of Warwick Coventry United Kingdom

ISBN: (纸本)9783031463341

Although the data-driven analysis of football players’ performance has been developed for years, most research only focuses on the on-ball event including shots and passes, while the off-ball movement remains a little-explored area in this domain. Players’ contributions to the whole match are evaluated segmentally and unfairly, those who have more chances to score goals earn more credit than others, while the indirect and unnoticeable impact that comes from continuous movement has been ignored. This research presents a novel deep-learning network architecture which is capable to predict the potential end location of passes and how players’ movement before the pass affects the final outcome. Once analyzed more than 28,000 pass events, a robust prediction can be achieved with more than 0.7 Top-1 accuracies. And based on the prediction, a better understanding of the pitch control and pass option could be reached to measure players’ off-ball movement contribution to defensive performance. Moreover, this model could provide football analysts a better tool and metric to understand how players’ movement over time contributes to the game strategy and final victory. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Network architecture

来源：评论

学校读者我要写书评

暂无评论

Seeing Through the Lies: A Vision Transformer-Based Solution 3rd

Seeing Through the Lies: A Vision Transformer-Based Solution

引用

3rd international conference on Artificial-Business Analytics, Quantum and machine learning: Trends, Perspectives, and Prospects, Com-IT-Con 2023

作者： Rasool, Aale Katarya, Rahul Big Data Analytics and Web Intelligence Laboratory Department of Computer Science Delhi Technological University New Delhi India

ISBN: (纸本)9789819725076

Deepfake technology has become increasingly sophisticated and poses a growing threat to society, as it can be used to create convincing fake videos for malicious purposes. Therefore, detecting deepfakes has become crucial to ensure the authenticity of visual content. This paper proposes a novel deepfake detection approach that utilizes InceptionResNetV2 for feature extraction and Vision Transformer (ViT) with Nyström Attention mechanism for classification. Our model achieves high accuracy, AUC, precision, and recall on the CelebDFv2 dataset and outperforms state-of-the-art techniques like EfficientNet, XceptionNet, and ResNet. We also perform evaluations on the CelebDFv1 and DFDC datasets. Furthermore, we conduct a comprehensive literature survey to highlight the existing research in deepfake detection. We provide a roadmap for future work in this field, highlighting potential research directions that can further improve the effectiveness and applicability of deepfake detection models. The proposed model shows great potential for real-world applications, and the suggested future work can help to address some of the remaining challenges in this area. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

machine learning Methods in Natural Language Information Extraction

Machine Learning Methods in Natural Language Information Ext...

引用

Intelligent Technologies (CONIT), international conference on

作者： Kejia Liu University of British Columbia Canada

Information extraction has become a research hotspot. According to the division of ACE (Automatic Content Extraction) conference evaluation tasks, the main research focuses on four areas: named entity recognition, entity relationship extraction, anaphora resolution, and event detection. Among them, entity recognition and relationship extraction are the most important parts of these tasks. machine learning is a branch of computer science. Its focus is on developing algorithms that can be used to solve problems in the fields of pattern recognition, classification, prediction, and data analysis. machine learning has been applied in NLP for several years. The most common machine learning technology in natural language processing (NLP) is called supervised learning. This technology involves training models using labeled data, where tags refer to the attributes or features of the training dataset. The goal is to predict which class or category should be assigned to a new unlabeled text sample based on prior knowledge of existing text attributes. This article focuses on machine learning and conducts research in the fields of natural language processing and transmission. In natural language processing, we first explore a general technology for generating word vectors, that is, integrating word embedding. By integrating the existing word embedding vector set and semantic knowledge base, we can generate a higher quality word embedding vector set.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Image Processing Techniques for Leaf Disease Detection based on ELM-SSA Approach 3

Image Processing Techniques for Leaf Disease Detection based...

引用

3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Kumar, A.Sasi Ramesh, M. Arpana, M. Sudarshanam, A. Velusudha, N.T. Suthar, Trilok Srinivas University Institute of Engineering & Technology Department of CSE Dakshina Kannada District Karnataka State India AVNIET Koheda Ibrahimpatnam Department of ECE India AVN Institute of Engineering and Technology Ibrahimpatnam Department of ECE Hyderabad India SR University School of Agriculture Telangana Warangal India Prince Shri Venkateshwara Padmavathy Engineering College Department of ECE Chennai India ADIT Department of IT CVM University Gujarat Anand India

ISBN: (纸本)9798350343632

Leaf diseases have emerged as a significant issue in agriculture due to their ability to significantly lower both the quality and quantity of harvests. If pests are not detected on crops and leaves in a timely manner, and an effective treatment is not administered, food insecurity, poverty, and mortality rates will rise. This demonstrates why automated leaf disease recognition is so crucial in the agricultural sector. Preprocessing, segmentation, feature extraction, and model training are all parts of the proposed technique. Preprocessing an image involves adjusting its data in order to remove unwanted distortions and boost other characteristics of the image that will be used later in analysis. The process of dividing a digital image into smaller images is called image segmentation. The proposed approach employed GLCM for the feature extraction process. Following the collection of features, ELM-SSA is used to train the models. The proposed method is superior to the ELM and SSA methods, which are both very popular. © 2023 IEEE.

关键词： Extreme learning machine (ELM) Leaf disease Salp Swarm Algorithm (SSA)

来源：评论

学校读者我要写书评

暂无评论

Research on Hybrid Remaining Usable Life Prediction Method Based on Battery Aging Model and data-Driven 3rd

Research on Hybrid Remaining Usable Life Prediction Method B...

引用

3rd international conference on machine learning, Cloud Computing and Intelligent mining, MLCCIM 2024

作者： Zhang, Yu Xu, Zhenyu Li, Dongqi Han, Shunjie Changchun University of Technology Changchun130012 China

ISBN: (纸本)9789819624676

Reliable prediction of the remaining useful life (RUL) of the battery is capable of providing a critical reference decision for users to use and replace batteries. Although there are many methods for battery RUL prediction, these methods suffer from insufficient training, ignoring local regeneration of capacity degradation curves, complex structure and a wide range of optimization seeking parameters, so this paper proposes a hybrid battery RUL prediction method. In the data processing stage, adaptive noise complete ensemble empirical modal decomposition (CEEMDAN) decomposes the battery capacity sequence, then calculates the fuzzy entropy value of each component and reconstructs the components with similar entropy values. In the model training stage, two data and model class methods, particle filtering to update the battery aging model parameters and Gaussian process regression (GPR) to fit the reconstructed components, are used respectively to further learn the long-term and local fluctuation parts of the battery capacity series. In the prediction stage, the prediction results of the two components are combined to obtain the predicted value of the future capacity of the battery and the uncertainty quantification of its RUL. Finally, the proposed hybrid model is validated on a battery dataset at different temperatures and experimental conditions, as a result, the RUL prediction method is shown to possess favorable prediction accuracy, good stability, and reliable uncertainty management capability. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

Vehicle Theft Detection Using Neural pattern recognition

Vehicle Theft Detection Using Neural Pattern Recognition

引用

Pervasive Computing and Social Networking (ICPCSN), international conference on

作者： J. Jane Rubel Angelina S.J Subhashini Anil Kumar Rapuri Vennela Ravva Raghavendra Rasala Sai Dcepak Ray Adurgam Dept of Computer Science and Engineering Kalasalingam Academy Of Research And Education Krishnankoil TamilNadu India Dept of Computer Science and Engineering SRM Madurai College for Engineering and Technology Sivagangai TamilNadu India

Finding stolen cars is becoming increasingly important in many urban regions. An automated system for scanning license plates can recognize vehicle numbers without the need for human interaction. This work proposes a vehicle theft detection system based on neural pattern recognition, gaussian filter, and equilibrium optimization. The proposed architecture has significant speedup and higher accuracy rates. The proposed number plate recognition method has a maximum accuracy rate of 94% and an average reduction in the processing time of 32%. pattern recognition is the process of detecting regularities and patterns in data using machine learning. These analogies may now be uncovered via statistical analysis, historical data, or machine-generated knowledge.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Combining the Clinical and Operational Perspectives in Heterogeneous Treatment Effect Inference in Healthcare Processes 3rd

Combining the Clinical and Operational Perspectives in Heter...

引用

3rd international conference on Process mining (ICPM)

作者： Verboven, Sam Martin, Niels Vrije Univ Brussel Data Analyt Lab Pleinlaan 2 B-1050 Brussels Belgium Hasselt Univ Res Grp Business Informat Martelarenlaan 42 B-3500 Hasselt Belgium Res Fdn Flanders FWO Egmontstr 5 B-1000 Brussels Belgium

ISBN: (纸本)9783030985813;9783030985806

Recent developments in causal machine learning open perspectives for new approaches that support decision-making in healthcare processes using causal models. In particular, Heterogeneous Treatment Effect (HTE) inference enables the estimation of causal treatment effects for individual cases, offering great potential in a process mining context. At the same time, HTE literature typically focuses on clinical outcome measures, disregarding process efficiency. This paper shows the potential of jointly considering the clinical and operational effects of treatments in the context of healthcare processes. Moreover, we present a simple pipeline that makes existing HTE machine learning techniques directly applicable to event logs. Besides these conceptual contributions, a proof-of-concept application starting from the publicly available sepsis event log is outlined, forming the basis for a critical reflection regarding HTE estimation in a process mining context.

关键词： Heterogeneous Treatment Effect Process mining machine learning Event Log

来源：评论

学校读者我要写书评

暂无评论

Authentication using Biometric data from Mobile Cloud Computing in Smart Cities 3

Authentication using Biometric Data from Mobile Cloud Comput...

引用

3rd international conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Salama, Ramiz Al-Turjman, Sinem Altrjman, Chadi Al-Turjman, Fadi Prakash, R.Om Yadav, Satya Prakash Vats, Satvik Ai and Robotics Institute Research Center for Ai and IoT Department of Computer Engineering Near East University Near East Boulevard TRNC Mersin 10 Nicosia99138 Turkey Ai and Robotics Institute Near Artificial Intelligence Engineering Dept Near East University Mersin10 Nicosia Turkey Waterloo University Department of Chemical Engineering ONN2L 3G1 Canada Noida Instue Engineering and Technology U.P Greator Noida201306 India Department of Computer Science and Engineering Greater Noida201306 India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350330724

Smart cities are cities that are designed to be more efficient, sustainable, and connected. As our cities grow and become more complex, it's important to find new ways to address the challenges that arise, such as security, privacy, and mobility. This is where mobile cloud computing and biometric authentication come in. Mobile cloud computing is a way to provide cloud computing services to mobile devices, which means people can access services and data from anywhere and at any time. Biometric authentication is a method of identifying people based on their unique physical or behavioral characteristics, like fingerprints, facial recognition, or voice recognition. These two technologies can be combined to create a secure and personalized environment for residents and visitors in smart cities. By using mobile devices, IoT devices, wireless sensor networks, and edge computing, we can collect real-time data that can be used for big data analytics and machine learning. This means we can optimize city services, like traffic management, waste management, or energy consumption, and enhance the quality of life for people living in smart cities. However, the use of these technologies also poses significant security and privacy risks, so it's important to design systems that are secure and privacy-preserving. This requires interdisciplinary research and collaboration between experts in different fields. In summary, mobile cloud computing and biometric authentication have the potential to transform smart cities by creating a more secure and personalized environment for residents and visitors. But we must also be mindful of the potential risks and work together to address them. © 2023 IEEE.

关键词： Mobile cloud computing

来源：评论

学校读者我要写书评

暂无评论

Based on the Application of machine learning Algorithms in Business data Analysis

Based on the Application of Machine Learning Algorithms in B...

引用

Smart Generation Computing, Communication and Networking (SMART GENCON), international conference on

作者： Yiwen Zhang The University of Auckland Auckland CBD Auckland

With the increasing complexity of business environment, the importance of data analysis in business decision-making has become increasingly prominent. As a powerful data analysis tool, machine learning algorithm has been widely used in the field of business data analysis. This paper will introduce the application of machine learning algorithm in business data analysis, including classification, clustering, prediction and association rule mining.

关键词：

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329页 << < 63 64 65 66 67 68 69 70 71 72 > >>

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：