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
142 册 图书
22 篇 期刊文献

馆藏范围

3,280 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,140 篇 工学
- 1,954 篇 计算机科学与技术...
- 1,096 篇 软件工程
- 404 篇 信息与通信工程
- 285 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
- 67 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
776 篇 理学
- 429 篇 数学
- 295 篇 生物学
- 151 篇 统计学（可授理学、...
- 148 篇 物理学
- 127 篇 系统科学
- 89 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
51 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
543 篇 machine learning
242 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...
110 篇 training
93 篇 data models
80 篇 neural networks
78 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 king fahd univer...
5 篇 uttaranchal univ...
5 篇 uttaranchal inst...
5 篇 institute of aut...
4 篇 indian institute...
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...

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

2,835 篇 英文
436 篇 其他
45 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 3281 条记录，以下是1331-1340 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：

3rd international conference on Recent Innovations in Computing, ICRIC 2020

3rd International Conference on Recent Innovations in Comput...

引用

3rd international conference on Recent Innovations in Computing, ICRIC 2020

ISBN: (纸本)9789811582967

The proceedings contain 69 papers. The special focus in this conference is on Recent Innovations in Computing. The topics include: Effect of Supercapacitor on Power Supply for Rechargeable Implanted Medical Devices;Particle Swarm Optimization and Genetic Mutation Based Routing Technique for IoT-Based Homogeneous Software-Defined WSNs;defining and Evaluating Network Communities Based on Ground-Truth in Online Social Networks;microstrip Patch Antenna with Truncated Edges for Bandwidth Improvement for Wireless Applications;a Deep Network Model for Paraphrase Detection in Punjabi;Design and Development of Software and Hardware Modules of Bioimpedance System Using LTSpice;Investigations on Various Designs of Dielectric Resonator Antennas (DRA) for C Band Applications;Planar Rectangular Micro-strip Patch Antenna Design for 25 GHz;intelligent Opportunistic Routing Protocol in Wireless Sensor Networks: A Security Perspective;machine learning-Based Information Retrieval System;OSEP: An Optimized Stable Election Protocol in Heterogeneous Wireless Sensor Networks;bot Detection in Social Networks Using Stacked Generalization Ensemble;internet of Things (IoT): Vulnerabilities and Remediation Strategies;DACHE: A data Aggregation-Based Effective and Optimized Cluster Head Election Routing Protocol for HWSNs;A Hybrid Approach with Intrinsic Feature-Based Android Malware Detection Using LDA and machine learning;towards recognition of Normal Versus Pneumonia Infected Patients Using Deep Neural Network Technique;edge Detection Using Guided Image Filtering and Ant Colony Optimization;A-VQA: Attention Based Visual Question Answering Technique for Handling Improper Count of Occluded Object;Wireless Sensing with Radio Frequency Identification (RFID): Instrumental in Intelligent Tracking;impact of Distortions on the Performance of Feature Extraction and Matching Techniques;fog Computing Enabled Healthcare 4.0.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Proceedings of the 2020 IEEE 3rd international conference on data Stream mining and Processing, DSMP 2020

Proceedings of the 2020 IEEE 3rd International Conference on...

引用

3rd IEEE international conference on data Stream mining and Processing, DSMP 2020

ISBN: (纸本)9781728132143

The proceedings contain 88 papers. The topics discussed include: information processing system for detection impurity in technical oil based on laser;hybrid machine learning system for solving fraud detection tasks;speech signal structuring method for biometric personality identification;kln: a deep neural network architecture for keypoint localization;training neural network over encrypted data;forecasting nonlinear nonstationary processes in machine learning task;the algorithmic classification trees;development of an adaptive module of the distance education system based on a hybrid neuro-fuzzy network;new approaches in the learning of complex-valued neural networks;trainable neural networks modeling for a forecasting of start-up product development;deep neo-fuzzy neural network and its accelerated learning;and two approaches to machine learning classification of time series based on recurrence plots.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Annotating Documents using Active learning Methods for a Maintenance Analysis Application 20

Annotating Documents using Active Learning Methods for a Mai...

引用

3rd international conference on Artificial Intelligence and pattern recognition (AIPR)

作者： Pope, James Terwilliger, Mark Connell, J. A. (Jim) Talley, Gabriel Blozik, Nicholas Taylor, David Univ North Alabama Florence AL 35632 USA Univ Montevallo Montevallo AL USA Univ Memphis Memphis TN 38152 USA

ISBN: (纸本)9781450375511

The aircraft cargo industry still maintains vast amounts of the maintenance history of aircraft components in electronic (i.e. scanned) but unsearchable images. For a given supplier, there can be hundreds of thousands of image documents only some of which contain useful information. Using supervised machine learning techniques has been shown to be effective in recognising these documents for further information extraction. A well known deficiency of supervised learning approaches is that annotating sufficient documents to create an effective model requires valuable human effort. This paper first shows how to obtain a representative sample from a supplier's corpus. Given this sample of unlabelled documents an active learning approach is used to select which documents to annotate first using a normalised certainty measure derived from a soft classifier's prediction distribution. Finally the accuracy of various selection approaches using this certainty measure are compared along each iteration of the active learning cycle. The experiments show that a greedy selection method using the uncertainty measure can significantly reduce the number of annotations required for a certain accuracy. The results provide valuable information for users and more generally illustrate an effective deployment of a machine learning application.

关键词： Active learning Document Classification

来源：评论

学校读者我要写书评

暂无评论

Research on Application of Tobacco Company Supply Chain Management Based on data mining Technology

Research on Application of Tobacco Company Supply Chain Mana...

引用

international conference on machine learning, Big data and Business Intelligence (MLBDBI)

作者： Dazhu Yan Xishan Branch of Kunming Tobacco Company Kunming Yunnan China

ISBN: (纸本)9781665417914

As the market economy becomes more diversified, competition among enterprises is increasing. As a technological product in the information age, data mining technology is applied to enterprise supply chain management to help improve management efficiency and enhance the core competitiveness of enterprises. In this regard, this article takes a tobacco company as an example, briefly explains the basic principles of data mining technology in the application of supply chain management, outlines the supply chain management process based on data mining technology, analyzes and explores the selection of partners based on fuzzy data mining, and aims to give Enterprise supply chain management better apply data mining technology to provide some useful references.

关键词： Supply chain management databases Supply chains Companies machine learning Reliability engineering Market research

来源：评论

学校读者我要写书评

暂无评论

Active Probing for Improved machine-Learned recognition of Network Traffic 1

引用

3rd international conference on machine learning for Networking (MLN)

作者： Anvari, Hamidreza Lu, Paul Univ Alberta Dept Comp Sci Edmonton AB Canada

ISBN: (数字)9783030708665

ISBN: (纸本)9783030708665;9783030708658

Information about the network protocols used by the background traffic can be important to the foreground traffic. Whether that knowledge is exploited via optimization through protocol selection (OPS) or through other forms of parameter tuning, a machine-learned classifier is one tool to identifying background traffic protocols. Unfortunately, global knowledge can be difficult to obtain in a dynamic distributed system like a shared, wide-area network (WAN). Previous techniques for protocol identification have focused on passive or end-point signals for classification. For example, end-to-end round trip time (RTT) can, especially when gathered as a time series, reveal a lot about what is happening on the network. Other related signals, such as bandwidth, and the number of retransmissions can also be used for protocol classification. However, as noted, these signals are typically gathered by passive means, which may limit their usefulness. We introduce and provide a proof-of-concept of active probing, which is the systematic and deliberate perturbation of traffic on a network for the purpose of gathering information. The time-series data generated by active probing improves our machine-learned classifiers because different network protocols react differently to the probing. Whereas passive probing might be limiting the time series observations to a period of steady state (e.g., saturated network), active probing forces the system out of that steady state. We show that active probing improves on prior work (with passive probing of RTT) by between 7% to 16% in additional accuracy (depending on the window size), and reaching 90% averages in precision, recall, and F1-scores.

关键词： machine-learned classifier Active probing Protocol selection data transfer Wide-area networks Fairness Shared network

来源：评论

学校读者我要写书评

暂无评论

data mining System for Predicting a Winning Cricket Team 16

Data Mining System for Predicting a Winning Cricket Team

引用

16th IEEE international conference on Industrial and Information Systems, ICIIS 2021

作者： Hasanika, Dinithi Dilhara, Roshani Liyanage, Dulanjali Bandaranayake, Asitha Deegalla, Sampath University of Peradeniya Faculty of Engineering Department of Computer Engineering Peradeniya 20400 Sri Lanka

ISBN: (纸本)9781665426374

Cricket is a two-team outdoor game that originated in England around the 19th century. This is played in 3 forms as twenty20, ODI, and Test matches. Due to the availability of data, researchers have been able to do statistical analysis of data for pattern recognition, to find factors affecting the game, and for outcome prediction. But due to the high uncertainty of the game, it has become very difficult to come up with a stable and accurate model. The outcome model also depends on the number of overs, match type, time period, and player combination among many other factors. This research focuses only on the ODI matches that were played between ICC full members;Australia, West Indies, Sri Lanka, Bangladesh, New Zealand, Ireland, India, Zimbabwe, Afghanistan, England, South Africa, and Pakistan. This outcome prediction is based on players' performances in a team and some features specific to the team and the match. The individual performance of batsmen, bowlers, and fielders are analyzed separately considering all-time ODI data. The combined performance of batsmen and bowlers was analyzed, and compared with individual performances using statistical methods. Association rule mining was used to find frequent winning player combinations. Match data from 2015 to 2020 were considered for the combined performance analysis and outcome prediction. For all these predictions we used data mining and machine learning techniques. © 2021 IEEE.

关键词： Statistical methods

来源：评论

学校读者我要写书评

暂无评论

Enhanced Biomedical Named Entity recognition Using SpaCy and BERT Models

Enhanced Biomedical Named Entity Recognition Using SpaCy and...

引用

3rd international conference on machine learning and data Engineering, ICMLDE 2024

作者： Kumar, Manish Singh, Pardeep Kashtriya, Poonam CSE Department JNGEC Sundernagar HP Mandi175018 India CSE Department NIT HP Hamirpur177005 India

Identification of named entity is a crucial procedure which entails locating and categorizing specified items in text, including people, places, organizations, medical codes, time expressions, amounts, and monetary amount. This paper concentrates on biomedical NER, which is vital for accurately identifying entities like diseases, chemicals, and drugs within biomedical research and clinical records. NER is crucial for applications including question-answering systems and automated extraction of information from large text corpora, as manually pinpointing these entities is both laborious and difficult. Automating this task with NER improves both efficiency and precision. The study evaluates and compares three biomedical NER models: SciBERT, a BERT-based model designed for scientific terminology;BlueBERT, trained with MIMIC-III clinical records and PubMed papers and SpaCy, a model pretrained with biomedical data. The methodology involves preprocessing the BioCreative V CDR (BC5CDR) biomedical text corpus for extracting chemical-disease relationships, annotating entities such as chemicals and diseases, getting the training dataset ready, and running the models through several training epochs. Performance is measured using metrics like accuracy, precision, recall, and F1-score, which provide insights into the effectiveness of each model architecture in biomedical NER. Results demonstrate that SciBERT having a remarkable 96.81% F1-score, followed by BlueBERT at 95.75%, and SpaCy at 90.96%. These results offer valuable guidance for researchers in choosing the most suitable model for developing automated systems to identify certain entities in the medical domain. © 2025 The Author(s).

关键词： Clock and data recovery circuits (CDR circuits)

来源：评论

学校读者我要写书评

暂无评论

Research on master data recognition of TCM based on analytic hierarchy process

Research on master data recognition of TCM based on analytic...

引用

2021 3rd international conference on Applied machine learning and data Science, ICAMLDS 2021

作者： Sang, Yuhui Tian, Shuanggui Hubei University of Chinese Medicine Wuhan China

With the rapid development of information technology in the field of medical and health, the requirement for information sharing was higher and higher. TCM plays an irreplaceable role in promoting health development. The information of TCM was represented by the construction, application and data sharing of information system, and faced complicated problems. data environment, standardized data management requirements and data standards were very important. In the field of TCM, the main line was about "TCM information integration standardization, TCM standards into information", while the main data was taken as the basis of data standardization. This paper through the investigation and summary of the existing information system and data items, according to theoretical research of main data recognition by scholars, discussed the main data identification method by using analytic hierarchy process, and extracted the main data, so as to improve quality of data management and optimize data management environment. © Published under licence by IOP Publishing Ltd.

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence Platform for Low-Cost Robotics 3

Artificial Intelligence Platform for Low-Cost Robotics

引用

3rd international conference on Signal Processing and Information Security, ICSPIS 2020

作者： Afsari, Kiyan Saadeh, Maha Middlesex University Dubai United Arab Emirates

ISBN: (纸本)9781728189987

The rise of Artificial Intelligence (AI) and robotics in the past decade has created various career opportunities in many industries such as robotics, manufacturing and healthcare. Thus, skills such as AI and robotics will play a critical role in the coming years. This project focuses on introduction of an AI platform for Low-cost robotics using MATLAB. The graphical based interface simplifies the task of design and implantation of machine learning functionalities such as object/pattern recognition and classification. The application offers three types of learning methods such as machine learning, Deep learning and Transfer learning. Currently, the end devices are Arduino based and raspberry pi processors. The communication can be wired or wireless. The MATLAB app is tested using an Arduino based Robot (DFRobot Turtle 2WD) and a Raspberry pi-based robot to achieve object recognition and voice recognition. © 2020 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Analysis of Hate Speech Detection and recognition Utilising Advanced machine learning Algorithms and Techniques 3

A Comprehensive Analysis of Hate Speech Detection and Recogn...

引用

3rd IEEE international conference on Automation and Computation, AUTOCOM 2025

作者： Mannepalli, Praveen Kumar Sharma, Saurabh Rajput, Neha Kalamdhad, Sanjay Chandigarh University Department of Computer Science & Engineering Mohali India Chandigarh University Department of Computer Science and Engineering Mohali India Chandigarh University Department of Computer Science and Engineering Punjab India St. Vincent Pallotti College of Engineering and Technology Department of Computer Science & Business System Nagpur India

ISBN: (纸本)9798331542375

Social networking sites have come into demand as a way of sharing ideas and opinions with other people. But unfortunately, people tend to misuse social media to write nasty comments. Victims' lives might be negatively impacted by behaviours that are abusive and humiliating. Social networks give people a great tool to share information on ideas on multiple topics and opinions. However, these platforms are often abused to announce toxic and offensive comments, which eventually negatively affect victims and demographics. This study offers a thorough method for identifying hate speech (HS) on social media by utilising cutting-edge ML algorithms. A publicly available Twitter dataset containing 159,571 tweets classified into six categories, including toxic and identity hatred, was utilised. The methodology comprises data collection, conditioning, and categorisation that employs BiLSTM, which is particularly appropriate for the tasks demanding contextual sensitivity. These operations include symbol removing, stemming and stop-word eliminating, feature extraction using TF-IDF, and using the Bag-of-Words model. For classification of the data between hate and non-hate, the dataset is then split into training and testing datasets and the BiLSTM model used to provide classifications for the text. The evaluation of the BiLSTM model demonstrates superior performance, achieving an accuracy86%, a precision90%, a recall86%, and an F1-score88% • A comparison between the model and other models such as SVM and CNN reveals the strength of the BiLSTM in contextual classification tasks. The results demonstrate that BiLSTM can tackle problems with hate speech detection, providing a strong answer to the problem of harmful content on social media and helping to make the internet a better place for everyone. © 2025 IEEE.

关键词： Tweets

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 << < 130 131 132 133 134 135 136 137 138 139 > >>

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：