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1311-1320 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：

Khasi Sign Language recognition using Google's Mediapipe and Deep learning Feedforward Neural Network Approach

Khasi Sign Language Recognition using Google's Mediapipe and...

引用

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

作者： Ranee, Lincolin Amory Marshillong, Ferdinand Lyngdoh Lyndoh, Saralin A. Maji, Arnab Kumar Department of Information Technology North-Eastern Hill University Shillong793022 India Department of Linguistic North-Eastern Hill University Shillong793022 India

Sign language is utilized by individuals who have difficulty hearing or speaking to communicate. Developing technology-assisted tools for interpreting sign language is critical, especially for regional languages such as Khasi Sign Language in India. This would significantly improve communication in indigenous languages. While substantial studies have been conducted on numerous world languages, there is still an opportunity to develop tools and strategies to support local Indian sign languages. This work attempts to utilize the advancement of deep learning to create a system capable of identifying gestures made by the hands in the low-resource Khasi Language. A 14,49,252 data point set was created to represent 18 static two-hand gestures related to the Khasi alphabet. These 18 static signs were derived from the alphabets of the Khasi language, including 'A', 'B', 'D', 'E', 'G', 'I', 'Ï', 'K', 'M', 'N', 'N', 'NG', 'P', 'R', 'S', 'T', 'U', and 'W'. Prior to extracting the hand landmarks using Mediapipe, we enhanced the raw image using the Contrast Limited Adaptive Histogram Equalization (CLAHE) method. This approach improves the visibility of images that are underexposed or lack contrast. A feedforward neural network model was developed for 18 signs of the Khasi alphabet. The proposed model attained an overall accuracy of 99% on the 3451 test images. This innovative approach can potentially revolutionize the communication barrier for individuals with speech and hearing difficulties in indigenous Indian languages by addressing a crucial need in the community. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Multilayer neural networks

来源：评论

学校读者我要写书评

暂无评论

Advances in Clustering Algorithms for Large-Scale data Processing with AI

Advances in Clustering Algorithms for Large-Scale Data Proce...

引用

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

作者： Sonal Sharma Vandana Singh Jeyalaxmi M Prasad B. Chaudhari Neeraj Das Avni Garg Computer Science and Engineering Jain (Deemed to be University) Bangalore Karnataka India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Department of Science and Humanities Prince Shri Venkateshwara Padmavathy Engineering College Chennai Department of Artificial Intelligence & Data Science Vishwakarma Institute of Information Technology Pune INDIA Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India

Clustering is a widely used technique in statistics mining for exploring and reading records with AI. It is an unsupervised gaining knowledge of technique, which may be used for exploratory facts evaluation. Clustering primarily aims to group similar statistics factors in a given facts set. In recent years, diverse advances in clustering algorithms have been developed for massive-scale record processing with AI. Some of the maximum popular clustering algorithms are ok-means, hierarchical clustering, fuzzy clustering, and spectral clustering. This kind of algorithm was used with AI for massive-scale records processing. Okay-approach and hierarchical clustering algorithms were widely used in diverse information mining responsibilities. They permit one to discover and organize the maximum similar statistics points. Fuzzy clustering and spectral clustering algorithms have become famous recently because of their capability to duplicate human perception and questioning when clustering records. Lately, deep learning techniques have been used with clustering algorithms to enhance their overall performance and boom the accuracy of records evaluation. Deep mastering is a subset of machine mastering which allows computers to research from repeated exposure to big datasets robotically. It permits clustering algorithms to investigate big-scale facts faster and more as it should be. Clustering with AI is an effective method for processing and analyzing huge-scale records. Recent advances in clustering algorithms and deep mastering strategies have improved performance and accuracy. Moreover, these algorithms may be used in diverse applications, which include client segmentation, community evaluation, and anomaly detection.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Detection of Skin Allergy Causing Chemicals in Textile Fibers using Principal Component Analysis and Support Vector machine 21

Detection of Skin Allergy Causing Chemicals in Textile Fiber...

引用

Proceedings of the 3rd international conference on Intelligent Science and Technology

作者： Jessie R. Balbin Gio Carlo F. Bautista Gella Mae J. Flores Matthew C. Teves School of EECE Mapua UniversityPhilippines Philippines

ISBN: (纸本)9781450388009

This paper presents the use of raspberry pi and an array of sensors to determine the various substances found in textile fabrics, mainly garments bought in fast fashion stores, which can be the cause of skin allergies. The support vector machine and principal component analysis machine learning algorithms are used to identify the type of skin allergy, the chemicals present and the type of fabric that was tested.

关键词： Skin Allergy Support Vector machine pattern recognition Principal Component Analysis Textile Fibers

来源：评论

学校读者我要写书评

暂无评论

Predicting the Prevalence Rate of COVID-19 Falsity on Temperature 11

Predicting the Prevalence Rate of COVID-19 Falsity on Temper...

引用

11th international conference on Cloud Computing, data Science and Engineering (Confluence)

作者： Rakhra, Ananya Gupta, Raghav Jain, Ishika Bhatia, Madhulika Amity Univ Amity Sch Engn & Technol Noida Uttar Pradesh India

ISBN: (纸本)9781665414517

COVID-19 originally known as Corona virus has been declared as pandemic by the World Health Organization on 11th March 2020. This infectious disease discovered from Wuhan, China in December 2019 and has affected millions of people around the world. Every country around the world is undergoing global economic crises and therefore, it' s the need of an hour to predict the prevalence and incidence of this disease throughout the world. This will help the medical practitioners and government agencies in India to make key decisions and appropriate measures to demystify the disease and prevent the country from global economic recession. This paper aims to analyze the number of cases in India by utilizing the machine learning techniques and exploratory data analysis to observe the growth patterns and map the increase in the frequency of those infected. The source of data was authentic COVID-19website which was showing confirmed diseased cases of Delhi, Uttar Pradesh and India as a whole. The count of confirmed cases taken from 14th March 2020 to 3rd September 2020 put together will help to know how effective the current efforts have been and also help to realize the need of working further to combat this virus. This research focuses on predicting the possible number of confirmed cases using techniques of data mining, data analysis with particularly regression, clustering and predictive analysis. The primary focus is to predict the number of cases in the coming month and finding out that whether there is relation between temperature with number of confirmed cases or not.

关键词： Pandemic Covid-19 Analysis Prediction data mining Regression Clustering

来源：评论

学校读者我要写书评

暂无评论

Feature selection and reduction of lower limb activity recognition based on surface electromyography and motion data 3

Feature selection and reduction of lower limb activity recog...

引用

2021 3rd international conference on Artificial Intelligence and Computer Science, AICS 2021

作者： Wei, Chunfeng Wang, Hong Hu, Fo Chen, Jichi Lu, Yanzheng Qi, Yangyang Department of Mechanical Engineering and Automation Northeastern University Liaoning Shenyang China

Daily activity recognition of lower limbs is of great significance to the health care of the elderly and patients with hemiplegia. Surface electromyography (sEMG) signal can directly reflect neuromuscular activity and is an important method for non-invasive monitoring of muscle activity on the body surface. In this paper, a novel method based on sEMG signal and inertial measurement unit (IMU) data to recognize daily activities of lower limbs is proposed. Record sEMG signals and IMU data of fifteen subjects using wearable sensor devices. After pre-processing such as filtering and sliding windows on the data, we extracted seventeen features. A feature selection method based on maximal relevance and minimal redundancy maximal relevance (mRMR) to select representative features. The selected features are input into four machine learning classifiers to classify four daily activities. The performance of the classifier is evaluated using accuracy and receiver operating characteristic curve-area under curve (ROC-AUC) score. The results show that the support vector machine has excellent performance in recognizing the daily activities of human lower limbs. © Journal of Physics: conference Series 2021.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

Reproducibility: Evaluating the Evaluations 3rd

Reproducibility: Evaluating the Evaluations

引用

3rd international Workshop on Reproducible Research in pattern recognition, RRPR 2021

作者： Lopresti, Daniel Nagy, George Lehigh University BethlehemPA18015 United States Rensselaer Polytechnic Institute TroyNY12180 United States

ISBN: (纸本)9783030764227

Evaluation is at the heart of reproducibility in research, and the related but distinct concept of replicability. The difference between the two is whether the determination is based on the original author’s source code (replicability), or is independent of the code and based purely on a written description of the method (reproducibility). A recent study of published machine learning experiments concluded that only two-thirds were reproducible, and that paradoxically, having access to the source code did not help with reproducibility, even though it obviously provides for replicability. Reproducibility depends critically, then, on the quality and completeness of both internal and external documentation. The growing popularity of competitions at pattern recognition conferences presents an opportunity to develop and disseminate new best practices for evaluating reproducibility. As an initial step forward, we collected the final reports and reviewed the competition websites associated with recent ICPR and ICDAR conferences. We used this data from 42 competitions to assess current practices and posit ways to extend evaluations from replicability (already checked by some competitions) to reproducibility on application-oriented data. We recommend empirical standards, monitoring competitions, and modified code testing to be considered and discussed by the research community as we all work together to advance the desirable goals of conducting and publishing research that achieves higher degrees of reproducibility. Competitions can play a special role in this regard, but only if certain changes are made in the way they are formulated, run, and documented. © 2021, Springer Nature Switzerland AG.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Research on Pulsar Classification Based on machine learning 3

Research on Pulsar Classification Based on Machine Learning

引用

3rd international conference on Intelligent Autonomous Systems (ICoIAS)

作者： Chen, Zhiyu Xu, Aiting Zhou, Yingying Gai, Yingjie Zhejiang Gongshang Univ Coll Stat & Math 18 Xuezheng Str Hangzhou 310018 Peoples R China

ISBN: (纸本)9781728160788

This paper uses pulsar signal data for data mining, on the basis of exploratory analysis, constructs a variety of classification models, such as Random Forest, SVM, Logical Regression, K-Nearest Neighbor, Naive Bayes, Decision tree, AdaBoost classifier, GBDT and XGBoost, to classify pulsar candidate samples. It is hoped that valuable suspected pulsar samples can be effectively screened from massive data for further observation and confirmation.

关键词： pulsar machine learning classification algorithm random forest

来源：评论

学校读者我要写书评

暂无评论

Medical data analysis using machine learning with knn 3rd

Medical data analysis using machine learning with knn

引用

3rd international conference on Innovative Computing and Communication, ICICC 2020

作者： Mohanty, Sabyasachi Mishra, Astha Saxena, Ankur Amity University NoidaUttar Pradesh India

ISBN: (纸本)9789811551475

machine learning has been used to develop diagnostic tools in the field of medicine for decades. Huge progress has been made in this area, however, a lot more work has yet to be done in order to make it more pertinent for real-time application in our day-to-day life. As a part of data mining, ML learns from previously fed data to classify and cluster relevant information. Hence, the main problems arise due to variations in the big data in the individuals and huge amounts of unorganised datasets. We have used ML to figure out various patterns in our dataset and to calculate the accuracy of this data, with the hope that this serves as a stepping stone towards developing tools that can help in medical diagnosis/treatment in future. Creating an efficient diagnostic tool will help improve healthcare to a great extent. We have used a mixed dataset where an individual with any severe illness in early stages or individuals who are further along, are both present. We use libraries like seaborn to construct a detailed map of the data. The fundamental factors considered in this dataset are age, gender, region of stay and blood groups. The main goal is to compare different data to each other and locate patterns within. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021.

关键词： data mining

来源：评论

学校读者我要写书评

暂无评论

Research on Electricity Information Acquisition System Based on Sample data mining Model 3

Research on Electricity Information Acquisition System Based...

引用

3rd international conference on Computer Information Science and Application Technology (CISAT)

作者： Dang Zhongkui Fu Lei State Grid NingXia Informat & Telecommun Co Guyuan 756000 Peoples R China

In power user information collection and detection, power companies generally have a variety of different detection needs, or need to solve the problem while having additional requirements for certain aspects. Therefore, the SVM classification technology is used in the paper to carry out more detailed pattern recognition of power consumption characteristics for small-scale users or users with major suspicions. Moreover, given the imbalance of the abnormal electricity detection data set, a comprehensive processing model of unbalanced samples is constructed. Meanwhile, the differential evolution algorithm is applied to complete the SVM parameter optimization, which not only solves the problem that the SVM classification performance is significantly affected by the parameters, but also ensures the operating efficiency of the integrated classification model.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Evaluation Model and Algorithm Based on Financial data 3

Evaluation Model and Algorithm Based on Financial Data

引用

3rd international conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021

作者： Hu, Shuyu Huang, Ming School of Economics and Management Hunan Open University Changsha China

ISBN: (纸本)9781450385046

The rapid development of the domestic financial market has increased the enthusiasm of various investors to participate, the amount of data and the frequency of transactions have increased sharply, the demand for transaction speed has increased, the correlation of data between markets has become more complex, and the proportion of quantitative exchanges has increased. Correspondingly, the proportion of quantitative transactions that use model algorithms in finance is increasing, making it possible to use pattern recognition to analyze financial data to guide quantitative transactions. The purpose of this article is to study the evaluation model and its algorithm based on financial data. Aiming at the shortcomings of the algorithm in the future financial market and the specific environment of the domestic financial market, this paper proposes to use the continuous hidden Markov model to analyze and predict financial data. This paper conducts a comprehensive research on the development and algorithm theory of the entire continuous hidden Markov model system, decomposes the model's identification, decoding, and learning processes, and conducts research on the application of the three types of processes in finance. At the same time, according to the specific financial data and the algorithmic process of the model, the stock and futures data are extracted and processed, and the model system sample data and various parameters are set using classification selection, wavelet denoising and stable index construction to improve the model under financial data. This paper uses actual transaction data to verify the entire model system, and then uses the recognition and decoding process to study the adaptability of the model, and concludes that the Hidden Markov Model can well identify the pattern features in financial data. Experimental research shows that the result of the hidden state is close to 80% similar to the original state. The continuous hidden Markov model can restore

关键词： Financial markets

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 << < 128 129 130 131 132 133 134 135 136 137 > >>

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：