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

2,967 篇 会议
174 册 图书
25 篇 期刊文献

馆藏范围

3,165 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

2,043 篇 工学
- 1,824 篇 计算机科学与技术...
- 959 篇 软件工程
- 330 篇 电气工程
- 313 篇 信息与通信工程
- 214 篇 控制科学与工程
- 207 篇 生物工程
- 149 篇 生物医学工程（可授...
- 71 篇 光学工程
- 64 篇 机械工程
- 62 篇 化学工程与技术
- 51 篇 电子科学与技术（可...
- 48 篇 仪器科学与技术
- 46 篇 安全科学与工程
- 36 篇 交通运输工程
649 篇 理学
- 352 篇 数学
- 245 篇 生物学
- 140 篇 物理学
- 135 篇 统计学（可授理学、...
- 95 篇 系统科学
- 63 篇 化学
408 篇 管理学
- 244 篇 图书情报与档案管...
- 182 篇 管理科学与工程(可...
- 83 篇 工商管理
262 篇 医学
- 241 篇 临床医学
- 123 篇 基础医学(可授医学...
- 74 篇 药学(可授医学、理...
- 40 篇 公共卫生与预防医...
46 篇 法学
- 42 篇 社会学
38 篇 教育学
- 32 篇 教育学
33 篇 经济学
- 31 篇 应用经济学
23 篇 农学
6 篇 艺术学
4 篇 文学

主题

573 篇 machine learning
564 篇 data mining
320 篇 pattern recognit...
209 篇 deep learning
201 篇 feature extracti...
154 篇 support vector m...
145 篇 artificial intel...
129 篇 machine learning...
120 篇 training
117 篇 accuracy
90 篇 data models
89 篇 data mining and ...
71 篇 neural networks
71 篇 classification
67 篇 predictive model...
66 篇 face recognition
61 篇 learning systems
52 篇 computer imaging...
50 篇 convolutional ne...
48 篇 classification a...

机构

9 篇 school of comput...
9 篇 chinese academy ...
8 篇 zhejiang univers...
8 篇 chitkara univers...
7 篇 guangdong univer...
7 篇 school of inform...
6 篇 xi'an university...
6 篇 indian statistic...
6 篇 central south un...
6 篇 department of co...
6 篇 unsw sydney
6 篇 xi'an university...
6 篇 southern univers...
5 篇 study group aust...
5 篇 peking universit...
4 篇 centre for patte...
4 篇 chongqing univer...
4 篇 national laborat...
4 篇 sun yat sen univ...
4 篇 school of inform...

作者

11 篇 de-shuang huang
8 篇 petra perner
7 篇 krasotkina olga
7 篇 mottl vadim
7 篇 ying tan
6 篇 zheng-guang wu
6 篇 ryszard tadeusie...
6 篇 marcin korytkows...
6 篇 phung dinh
6 篇 venkatesh svetha
6 篇 hongyi li
6 篇 jacek m. zurada
6 篇 chaojie li
6 篇 biao luo
6 篇 ilias maglogiann...
6 篇 lotfi a. zadeh
6 篇 leszek rutkowski
6 篇 lazaros iliadis
6 篇 long cheng
5 篇 vitoantonio bevi...

语言

2,998 篇 英文
154 篇 其他
25 篇 中文
1 篇 土耳其文

检索条件"任意字段=5th International Conference on Machine Learning and Data Mining in Pattern Recognition"

共 3166 条记录，以下是851-860 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：

Genetic-Algorithm-Based Hierarchical Echo State Network for Temperature Prediction

Genetic-Algorithm-Based Hierarchical Echo State Network for ...

引用

machine learning and Computer Application (ICMLCA), international conference on

作者： Sheng Yang Shuaiheng Li Jinghang Research Institute of Computing and Communication Beijing China

ISBN: (数字)9798331530334

ISBN: (纸本)9798331530341

data-driven based temperature prediction methods are now highly competitive against numerical weather prediction (NWP) method. However, most deep learning-based prediction models focus on global weather forecasting, which requires substantial computational and data resources. Additionally, these models often exhibit lower accuracy in predicting temperatures in the upper atmosphere, which is crucial for studying the near space. To solve this problem, in this paper, the genetic-algorithm-based hierarchical echo state network (GA-HESN) is proposed. Firstly, the hierarchical architecture can fully extract information from the input sequence. Secondly, a parameter optimization strategy based on the genetic algorithm is proposed to further enhance the network's precision. Finally, experiments on the upper atmosphere temperature dataset for the Beijing region demonstrate the effectiveness of the model.

关键词： Accuracy Atmospheric modeling Computational modeling Weather forecasting Computer architecture Predictive models Prediction algorithms Numerical models data mining Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Research on Face Attribute Privacy Protection Method Based on Multi task learning

Research on Face Attribute Privacy Protection Method Based o...

引用

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

作者： Fenfei Gu Eric Blancaflor Mideth Abisado College of Computing and Information Technologies National University Manila Philippines School of Big Data and Artificial Intelligence Anhui Xinhua University Hefei China School of Information Technology Mapua University Manila Philippines

With the widespread application of facial image recognition in fields such as finance, social media, and transportation, the privacy data of facial images is also frequently leaked. In order to effectively protect facial images, the protection of facial attributes is particularly important. therefore, this article combines the method of multi task learning to divide deep learning models into low-level models and top-level models. the underlying model serves as a data feature extractor; the top-level model serves as a classifier, specifically responsible for three tasks in multi task learning: business classification, privacy protection, and image restoration. the goal of the business classification task is to identify user facial attributes; the goal of privacy protection tasks is to minimize the inclusion of privacy related feature information in data features as much as possible; the goal of image restoration task is to make it difficult to recover the original image containing privacy attributes from the extracted data features. In order to measure the privacy of the data feature extractor, a loss function is set for each task, and finally, the loss functions of these three tasks are fused to obtain a data feature extractor that can protect privacy. Finally, through experimental data analysis, this method ensures both the accuracy of facial image recognition and the leakage of facial attribute privacy data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Model Selection and Evaluation for learning Analytics via Interpretable machine learning

Model Selection and Evaluation for Learning Analytics via In...

引用

Computer Science and Technologies in Education (CSTE), international conference on

作者： Zhuoran Li Zehui Zhan Department of Economics Department of Statistics University of Washington Seattle USA School of Information Technology in Education South China Normal University Guangzhou China

learning analytics is one of the most crucial tasks in understanding the relationship between learners' learning behaviors and academic performance in MOOCs. machine learning methods that enable us to learn the pattern of complex data make it more effective to conduct learning analytics. However, among a variety of models, only some of them can provide us with sufficient interpretability to understand the modeling result and propose pedagogically instructive suggestions for improving learners' learning strategies. By demonstrating the performance and interpretability of 17 machine learning models, this study would select the CART, which could balance the model performance and interpretability well, as the optimal model for learning analytics in MOOCs. through the further study of the CART, we concluded that the social interaction behaviors and prompt completion of learning tasks could most significantly help with improving learners' academic performance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Deep learning Approach for Kannada Handwritten Character recognition

A Deep Learning Approach for Kannada Handwritten Character R...

引用

Emerging Technology (INCET), international conference for

作者： U K Samarth Srushthi Joshi Satish Chikkamath Nirmala S R Suneeta Budihal dept. of electronics and communication KLE Technological University Hubli India

ISBN: (数字)9798350361155

ISBN: (纸本)9798350361162

Handwritten character recognition is a crucial process that involves converting handwritten text on different surfaces, such as paper and postcards, into digital formats, making it distinguishable from scanned images. Remarkable advancements have been made in this field, particularly in India, where many languages with complex scripts like Kannada, English, and Marathi are used. Kannada is one of the widely used languages in southern India, and recognizing its handwritten characters is challenging due to its complicated script. the article explains how CNN, a type of dense net, is used to recognize Kannada's handwritten characters. this technology can help protect many historical documents from damage and destruction, which is a significant achievement. the article also highlights that the versatility of this machine learning model extends beyond Kannada and can be used in various applications and technology development. the proposed research has used CNN and transfer learning due to its efficient layers, and the data set from Kaggle consisted of 16 classes of 25 images each for experimentation. the results showed a remarkable 97.50 percent accuracy in 50 epochs, demonstrating the potential of the CNN network in character recognition.

关键词： Deep learning Handwriting recognition Accuracy Navigation Transfer learning data augmentation data models

来源：评论

学校读者我要写书评

暂无评论

Sarcasm Prediction Using Different learning Approaches on User Behavior and Contextual Evaluation 5

Sarcasm Prediction Using Different Learning Approaches on Us...

引用

5th international conference on Information Management and machine Intelligence, ICIMMI 2023

作者： Ahire, Lomesh Kautik Babar, S.D. Mahalle, P.N. Dept of Computer Engineering Smt. Kashibai Navale College of Engineering Savitribai Phule Pune University Pune India Dept of Computer Engineering Savitribai Phule Pune University Pune India Dept. of Artificial Intelligence and Data Science Vishwakarma Institute of Information Technology Pune India

ISBN: (纸本)9798400709418

A large number of people have been using social media platforms extensively to communicate their thoughts and feelings in the recent era of social networking. Both the user base and data volume on social networks are growing quickly every day. Any time an event or activity occurs nearby, nearby individuals express their thoughts and reactions on social media. When a new product is introduced, users on social media platforms also comment on it. Some people express their views or feelings using informal or complex language which makes it difficult to understand for another user. It is challenging to ascertain the true thoughts because different people express their opinions in complex ways. In this study, the various factors that affect these feelings are briefly discussed. In order to identify sarcasm on Twitter, a generic technique is also necessary in addition to the tweet's content. the proposed approach uses contents of tweet in association with important aspects like user behavior and context of tweet. By users' behavior we can identify its influence on other users and context is required to identify user behavior while detecting sarcasm. Proposed approach uses user behavior pattern and personality features along with contextual data. this all information and the already known sarcasm prediction mechanism will help us to set up the generic approach to detect sarcasm on Twitter. © 2023 ACM.

关键词： Behavioral research

来源：评论

学校读者我要写书评

暂无评论

Stacked Convolutional Autoencoder with Multi-label Extreme learning machine (SCAE-MLELM) for Bangla Regional Language Classification 22

Stacked Convolutional Autoencoder with Multi-label Extreme L...

引用

5th international conference on Signal Processing and machine learning, SPML 2022

作者： Hossain, Prommy Sultana Chakrabarty, Amitabha Piran, Jalil Suh, Doug Young Department of Computer Science and Engineering Brac University Dhaka Bangladesh Department of Computer Science and Engineering Sejong University Seoul Korea Republic of Department of Electronic Engineering Kyung Hee University Seoul Korea Republic of

ISBN: (纸本)9781450396912

Several studies emphasized the importance of detecting the dialect spoken by the user, to improve customer-agent relationships in call centers operated by telecomunication companies. and to create advanced speech recognizing Artificial Intelligence devices using machine learning (ML) techniques. However, the extensive Bangla speech recognition research performed in the past did not address this issue. therefore, in this paper, we propose a model that uses deep learning (DL) techniques, as a subset of ML, to classify the regional language in the audio signal of the Bangla speech. We build a model based on Stacked Convolutional Autoencoders (SCAE) and Multi-label Extreme learning machines (MLELM). SCAE extracts the spatial and temporal features from the input data and produces a detailed feature vector. In order to provide a soft classification score and hard labels, the information is passed onto a series of MLELM networks. For Bangla speech dataset created during this research, the proposed method produced an accuracy score of 95%. Furthermore, the proposed system performs remarkably well in classifying the age and gender of the speaker in Bangla. © 2022 Association for Computing machinery.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Research on Match Competition Prediction Algorithm Based on LightGBM

Research on Match Competition Prediction Algorithm Based on ...

引用

pattern recognition and Artificial Intelligence (PRAI), international conference on

作者： Haiyan Zhang Xu Liu Wanyu Chen Guihua Gan Electronic Countermeasures Academy National University of Defense Technology Hefei China

ISBN: (数字)9798350350890

ISBN: (纸本)9798350350906

With the advent of the era of big data, artificial intelligence and machine learning have developed rapidly. At present, there are many competitive competition data, which can objectively predict the level of players in the future through data analysis. Firstly, based on the data of Wimbledon men's singles in 2023, this paper preprocesses and constructs the index system, and carries out the consistent processing and correlation analysis of the indicators. Among them, player 1 serve depth, player 1 serve speed, player 2 serve speed, player 1 break success rate, player 2 break success rate are the most positively correlated, and finally 5 indicators are determined. then, the LightGBM prediction algorithm is established to train the 185 games data of five matches, and the results of 42 games in the next game are predicted. the prediction accuracy is 83.72%. Compared with the random forest algorithm and ridge regression, the prediction algorithm has the highest accuracy. Finally, the LightGBM prediction competition fluctuation model was applied to other players, and it was found that the prediction accuracy of the model was 86.21 %. the prediction results show that the generalization effect of LightGBM algorithm is better, which provides a scientific basis for the level prediction of players in competitive competitions.

关键词： Accuracy machine learning algorithms Systematics Games Predictive models Prediction algorithms pattern recognition Indexes Random forests Sports

来源：评论

学校读者我要写书评

暂无评论

Automated Emotion recognition from Facial Expressions using Convolutional Neural Network

Automated Emotion Recognition from Facial Expressions using ...

引用

data Analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), international conference on

作者： Syed Aman Hussain Nareddy Yashwanth Reddy Junnuthula Srivardhan Ajay Sharma Shamneesh Sharma Saikat Gochhait School of Computer Science and Engineering Lovely Professional University Phagwara Punjab India Delivery and Student Success upGrad Education Private Limited Bangalore Karnataka India Symbiosis Institute of Digital and Telecom Management Constituent of Symbiosis International Deemed University Pune India

ISBN: (数字)9798350368710

ISBN: (纸本)9798350368727

In the era of digital communication, it is more about being able to detect emotions than anything else if we are to maintain this complicated and demanding human society. Emotion recognition research is pulling out all the stops, resulting in all manner of methods to recognize human feelings. Emotions are often transmitted through words and body language, and facial expressions play an important part in communicating them. In this paper, the use of a Convolutional Neural Network (CNN) is proposed as a real-time emotion recognition system based on machine learning algorithm, and the system is able to process video feeds. the classifier breaks emotions down into seven categories, with an accuracy of about 81 percent. In addition, the research extends to the use of various image datasets to improve emotion forecasting accuracy.

关键词： Industries Emotion recognition Accuracy machine learning algorithms Streaming media Digital communication Real-time systems Convolutional neural networks Feeds Forecasting

来源：评论

学校读者我要写书评

暂无评论

Power Management in Smart Residential Building with Deep learning Model for Occupancy Detection by Usage pattern of Electric Appliances 23

Power Management in Smart Residential Building with Deep Lea...

引用

5th international Electronics Communication conference, IECC 2023

作者： Lee, Sangkeum Nengroo, Sarvar Hussain Jin, Hojun Doh, Yoonmee Lee, Chungho Heo, Taewook Har, Dongsoo Daejeon34129 Korea Republic of Daejeon34141 Korea Republic of

ISBN: (纸本)9798400708855

With the growth of smart building applications, occupancy information in residential buildings is becoming more and more significant. In the context of the smart buildings' paradigm, this kind of information is required for a wide range of purposes, including enhancing energy efficiency and occupant comfort. In this study, occupancy detection in residential building based on technical information of electric appliances is implemented using deep learning. the dataset of electric appliances, sensors, light, and HVAC, that is measured by smart metering system and collected from 50 households is used for simulations. To classify the occupancy among datasets, support vector machine and autoencoder algorithm are used. the proposed autoencoder uses the GCN-GRU layers. Confusion matrix is utilized for accuracy, precision, recall, and F1 to demonstrate the comparative performance of the proposed method in occupancy detection. the proposed algorithm achieves occupancy detection using technical information of electric appliances by 95.7g1/498.4%. To validate occupancy detection data, principal component analysis and the t-distributed stochastic neighbor embedding (t-SNE) algorithm are employed. Power consumption with renewable energy system is reduced to 11.1g1/413.1% in smart buildings by using occupancy detection. © 2023 ACM.

关键词： Power management

来源：评论

学校读者我要写书评

暂无评论

5th international conference on Applied Informatics, ICAI 2022

5th International Conference on Applied Informatics, ICAI 20...

引用

5th international conference on Applied Informatics, ICAI 2022

ISBN: (纸本)9783031196461

the proceedings contain 32 papers. the special focus in this conference is on Applied Informatics. the topics include: Statistical Characterization of Image Intensities in Regions Inside Arteries to Facilitate the Extraction of Center Lines in Atherosclerosis Frameworks;Text Encryption with Advanced Encryption Standard (AES) for Near Field Communication (NFC) Using Huffman Compression;a Systematic Review on Phishing Detection: A Perspective Beyond a High Accuracy in Phishing Detection;application of Duality Properties of Renyi Entropy for Parameter Tuning in an Unsupervised machine learning Task;preliminary Study for Impact of Social Media Networks on Traffic Prediction;website Phishing Detection Using machine learning Classification Algorithms;AESRSA: A New Cryptography Key for Electronic Health Record Security;Detection of COVID-19 Using Denoising Autoencoders and Gabor Filters;development of a Mobile Application to Save Lives on Catastrophic Situations;COVID-19 Article Classification Using Word-Embedding and Different Variants of Deep-learning Approach;internet of things with Wearable Devices and Artificial Intelligence for Elderly Uninterrupted Healthcare Monitoring Systems;a Wayuunaiki Translator to Promote Ethno-Tourism Using Deep learning Approaches;rating the Acquisition of Pre-writing Skills in Children: An Analysis Based on Computer Vision and data mining Techniques in the Ecuadorian Context;study Techniques: Procedure to Promote the Comprehension of Texts in University Students;TPACK and Toondoo Digital Storytelling Tool Transform Teaching and learning;Fully Automated Lumen Segmentation Method and BVS Stent Struts Detection in OCT Images;predictive Modeling Toward the Design of a Forensic Decision Support System Using Cheiloscopy for Identification from Lip Prints;Automotive Industry Applications Based on Industrial Internet of things (IIoT). A Review;implementation of an IoT Architecture for Automated Garbage Segregation;architecture on Knowledge Managem

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317页 << < 82 83 84 85 86 87 88 89 90 91 > >>

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：