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

6,718 篇 会议
329 册 图书
119 篇 期刊文献

馆藏范围

7,165 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

4,791 篇 工学
- 3,970 篇 计算机科学与技术...
- 2,033 篇 软件工程
- 808 篇 电气工程
- 771 篇 信息与通信工程
- 592 篇 控制科学与工程
- 395 篇 生物工程
- 381 篇 生物医学工程（可授...
- 297 篇 光学工程
- 296 篇 机械工程
- 213 篇 仪器科学与技术
- 182 篇 电子科学与技术（可...
- 138 篇 化学工程与技术
- 128 篇 材料科学与工程（可...
- 120 篇 网络空间安全
- 108 篇 安全科学与工程
- 91 篇 动力工程及工程热...
1,629 篇 理学
- 809 篇 数学
- 494 篇 物理学
- 490 篇 生物学
- 273 篇 统计学（可授理学、...
- 190 篇 化学
- 141 篇 系统科学
844 篇 管理学
- 463 篇 管理科学与工程(可...
- 425 篇 图书情报与档案管...
- 181 篇 工商管理
679 篇 医学
- 604 篇 临床医学
- 254 篇 基础医学(可授医学...
- 145 篇 药学(可授医学、理...
- 100 篇 公共卫生与预防医...
122 篇 法学
- 115 篇 社会学
92 篇 教育学
58 篇 农学
52 篇 经济学
43 篇 艺术学
12 篇 文学
4 篇 军事学
1 篇 哲学

主题

927 篇 pattern recognit...
800 篇 artificial intel...
447 篇 machine learning
291 篇 feature extracti...
243 篇 deep learning
203 篇 accuracy
185 篇 support vector m...
134 篇 data mining
128 篇 training
126 篇 neural networks
126 篇 face recognition
103 篇 local binary pat...
103 篇 computer imaging...
102 篇 computer vision
88 篇 image processing...
87 篇 real-time system...
87 篇 convolutional ne...
85 篇 information syst...
83 篇 pattern matching
83 篇 computational mo...

机构

39 篇 chitkara univers...
33 篇 maharishi school...
27 篇 school of comput...
27 篇 indian stat inst...
25 篇 centre of interd...
25 篇 the islamic univ...
23 篇 department of ar...
23 篇 concordia univ c...
22 篇 national univers...
20 篇 school of comput...
19 篇 univ chinese aca...
18 篇 school of comput...
18 篇 univ waterloo de...
17 篇 vishwakarma inst...
16 篇 national laborat...
15 篇 school of artifi...
15 篇 institute of aut...
14 篇 lovely professio...
14 篇 uttaranchal inst...
14 篇 college of pharm...

作者

54 篇 suen ching y.
24 篇 suen cy
22 篇 kamel mohamed s.
18 篇 lu bao-liang
18 篇 karray fakhri
17 篇 de-shuang huang
17 篇 abraham ajith
14 篇 maji pradipta
13 篇 dash yajnaseni
12 篇 c.y. suen
10 篇 liu cheng-lin
10 篇 venkatesh svetha
10 篇 wong alexander
10 篇 chauhan rahul
10 篇 natarajan s.
10 篇 zheng wei-long
10 篇 liu wei
10 篇 vinay a.
9 篇 zhang lei
9 篇 gill kanwarparta...

语言

6,735 篇 英文
403 篇 其他
65 篇 中文
1 篇 土耳其文

检索条件"任意字段=3rd International Conference on Pattern Recognition and Machine Intelligence"

共 7166 条记录，以下是1151-1160 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 Accounting Data Encryption Processing System based on Artificial intelligence 3

Research on Accounting Data Encryption Processing System bas...

引用

3rd international conference on machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT2023

作者： Yao, Li Jin, Minyan College of Accounting Zhanjiang Science and Technology College Guangdong Zhanjiang524009 China

To address the issues of low confidentiality and poor real-time performance in the encryption process of accounting system data, a proposed solution based on artificial intelligence is presented. Firstly, by studying the knowledge and reasoning abilities utilized by artificial intelligence technology to simulate human experts in solving complex problems, the fundamental structure of the accounting system is obtained. Then, the data prior to encryption is processed using the wavelet denoising method to eliminate noise points from the data. Additionally, a chaotic parameter modulation encryption method is introduced, utilizing a logistic chaotic mapping model to modulate the data parameters. Simultaneously, during encryption and decryption analysis, iterative criteria for data parameters are established to reduce the number of iterations and achieve real-time data encryption. Finally, experimental results demonstrate that this method possesses higher efficiency in terms of real-time performance, integrity, and confidentiality, providing superior real-time data encryption capabilities. © 2023 The Authors. Published by Elsevier B.V.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Deep Learning for Enhanced Spectrum Sensing in Cognitive Radio Networks with Blockchain-based Security 3

Deep Learning for Enhanced Spectrum Sensing in Cognitive Rad...

引用

3rd IEEE international conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Solanki, Surendra Brahma, Banalaxmi Manipal University Jaipur Department of Artificial Intelligence & Machine Learning Rajasthan Jaipur India Dr. B. R Ambedkar National Institute of Technology Department of Computer Science and Engineering Punjab Jalandhar India

ISBN: (数字)9798350354348

ISBN: (纸本)9798350354348

The growing need for wireless communication requires the optimum use of spectrum. Cognitive Radio (CR) technology enables the utilization of unused frequency channels through the identification and exploitation of these bands. Nevertheless, conventional spectrum sensing approaches are plagued by drawbacks such as instances of missed detections and false alarms. This study presents a new framework that combines deep learning and blockchain technology to improve the accuracy of spectrum sensing and ensure safe spectrum management in cognitive radio networks. Deep learning models are highly proficient at acquiring intricate signal characteristics, which allows them to attain exceptional performance in spectrum sensing. Blockchain technology, characterized by its decentralized recordkeeping system, inability to be altered, and methods for reaching agreement, promotes confidence and thwarts tampering with spectrum sensing data and user access privileges. Our platform utilizes deep learning models on CR devices to achieve precise spectrum sensing. Additionally, it leverages the secure data storage and access control features of blockchain. This integration improves the accuracy of spectrum sensing, guarantees secure and transparent management of the spectrum, and encourages efficient utilization of the spectrum in cognitive radio networks. The evaluation technique and anticipated results are well defined, setting the stage for future investigations in this field. © 2024 IEEE.

关键词： Radio systems

来源：评论

学校读者我要写书评

暂无评论

Multilingual Speech Sentiment recognition Using Spiking Neural Networks 11th

Multilingual Speech Sentiment Recognition Using Spiking Neur...

引用

11th international conference on Big Data and Artificial intelligence, BDA 2023

作者： Parashar, Shreya Srinivasa, K.G. Department of Computer Science and Engineering IIIT Naya Raipur Chhattisgarh493661 India Department of Data Science and Artificial Intelligence IIIT Naya Raipur Chhattisgarh493661 India

ISBN: (纸本)9783031496004

Speech sentiment and emotion recognition has grown significantly as a research field in recent years as it has potential uses in a variety of domains. Multilingual speech sentiment recognition still remains a challenging task due to the cultural and linguistic differences in the speech. Although several approaches, particularly those based on deep learning techniques (ANNs), have shown encouraging outcomes in speech sentiment recognition, there remain obstacles in accurately representing the temporal and dynamic fluctuations in sentiments conveyed through speech. Spiking Neural Networks (SNNs), which have shown promising result in other machine learning and pattern recognition applications, such as handwriting and facial expression detection, are a potentially successful approach to deal with these challenges. In this research, we present a system for multilingual speech sentiment recognition using spiking neural networks. We have used Mel-frequency-cepstral coefficients (MFCC) features to train the model. Experiments are conducted on the data created by combining four datasets SAVEE (English), EMO-DB (German), EMOVO (Italian), and CaFE (French). We compared the performance of SNNs with ANNs such as MLP and RNN. In our experiments, spiking neural network achieves 76.85% of accuracy and outperforms its counterpart ANN models on this task. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Improving Diabetes Mellitus Prediction with MICE and SMOTE for Imbalanced Data 3

Improving Diabetes Mellitus Prediction with MICE and SMOTE f...

引用

3rd international conference on Artificial intelligence and Data Sciences, AiDAS 2022

作者： Abdullah, Mohammad Nasir Wah, Yap Bee Universiti Teknologi Mara Faculty of Computer and Mathematical Sciences Department of Statistics Perak Tapah35400 Malaysia Unitar International University Selangor Petaling Jaya47301 Malaysia

ISBN: (数字)9781665491648

ISBN: (纸本)9781665491648

Diabetes Mellitus is a chronic disease, and it affects our body nerves, eyes, kidney, and heart if not treated from the early stage. Clinical data faces issue of missing values due to lost in follow up of the patients imbalanced data. The aim of this study is to develop a Diabetes Mellitus prediction model using machine learning (ML) classifiers for an imbalanced dataset missing value. The PIMA Indian Diabetes Dataset was obtained from UCI machine learning repository. Data pre-processing involves data imputation using Multivariate Imputation Chained Equation (MICE) by Permutation Mean Matching method. Then the data was balanced using SMOTE and ROSE method. Results showed that the F-measure of the ML classifiers is higher under SMOTE oversampling technique. The random forest classifier has the highest F-measure (0.8307). The important features identified based on random forest classifier were glucose, BMI, and age. SMOTE technique is a good oversampling technique for imbalanced data. © 2022 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Veinseg-Net: A Novel Finger Vein Segmentation Algorithm Based on Deep Learning 23

Veinseg-Net: A Novel Finger Vein Segmentation Algorithm Base...

引用

3rd international conference on Bioinformatics and Intelligent Computing, BIC 2023

作者： Xu, Hong Wang, Peng Sun, Yewei Ye, Caizeng School of Software Shandong University Jinan250101 China Jinan Engineering Polytechnic Jinan250200 China Hazen and Sawyer 4035 Ridge Top Rd Suite 500 FairfaxVA22030 United States Shandong Institute of Commerce and Technology Jinan250103 China National Agricultural Products Modern Logistics Engineering Technology Research Center Jinan250103 China

ISBN: (纸本)9798400700200

On the basis of the original U-Net and ResNet finger vein segmentation methods, this paper proposes a new finger vein segmentation method based on the combination of the above two methods. This method completes feature extraction by using depth residual network instead of U-Net. Using extended convolution instead of traditional convolution solves the risk of loss of finger vein information extracted by pooling layer, so that the method can extract finger vein veins more accurately without pooling. The algorithm uses the Mish constructor to replace the ReLU constructor to strengthen the anti-compression ability of the model and make vein image more continuous. From the comparison of experimental results, it is not difficult to see that the segmentation accuracy of the newly proposed Veinseg-Net network on multiple finger vein databases are better than those of other depth learning segmentation methods. The good segmentation accuracy of finger vein image can help the finger vein recognition process in the subsequent environment intelligence. © 2023 ACM.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Investigating the Benefits of machine Learning Algorithms for Text Classification 3

Investigating the Benefits of Machine Learning Algorithms fo...

引用

3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Gowrishankar, J. Vinithra Banu, T. Parikshit, N. Singh, Vandana Kalra, Hitesh Sahoo, Girija Shankar Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Ramnagar562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Artificial Intelligence & Data Science Pune India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350319125

This paper affords a research into using gadget studying algorithms for textual content category duties, with a focal point on understanding the importance of these algorithms and their ability to enhance the accuracy of textual content classification. it's miles located that, while conventional techniques, which include rule based models and hand-engineered features, can attain first-class outcomes, there are compelling motives to explore the capability of device getting to know algorithms to further improve the accuracy and performance of textual content class. The paper discusses the 3 maximum famous gadget gaining knowledge of algorithms for this project: the NaÏve Bayes classifier, help Vector machines, and synthetic Neural Networks, and presents a top level view of the latest research findings that demonstrate the prevalence of these algorithms over traditional methods. The paper additionally presents an outline of the distinctive approaches for introducing era into text type, and discusses modern-day strategies for implementing and deploying those algorithms. Finally, the paper outlines ability areas for destiny research associated with information the results of system studying algorithms for this mission, and suggests viable instructions for exploration. © 2023 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

3rd international conference on Next Generation Arithmetic, CoNGA 2022

3rd International Conference on Next Generation Arithmetic, ...

引用

3rd international conference on Next Generation Arithmetic, CoNGA 2022

ISBN: (纸本)9783031097782

The proceedings contain 8 papers. The special focus in this conference is on Next Generation Arithmetic. The topics include: A Posit8 Decompression Operator for Deep Neural Network Inference;qtorch+: Next Generation Arithmetic for Pytorch machine Learning;ACTION: Automated Hardware-Software Codesign Framework for Low-precision Numerical Format SelecTION in TinyML;multiPosits: Universal Coding of Rn;comparing Different Decodings for Posit Arithmetic;universal: Reliable, Reproducible, and Energy-Efficient Numerics.

关键词：

来源：评论

学校读者我要写书评

暂无评论

2021 3rd international conference on Robotics, Intelligent Control and Artificial intelligence, ICRICA 2021

2021 3rd International Conference on Robotics, Intelligent C...

引用

2021 3rd international conference on Robotics, Intelligent Control and Artificial intelligence, ICRICA 2021

The proceedings contain 94 papers. The topics discussed include: stress analysis of key components of finger rehabilitation exoskeleton robot based on finite element method;design of intelligent wireless laser engraving machine;a flexible under-driven bionic climbing robot design;longitudinal driving force distribution of four in-wheel motors drive electric vehicle based on fuzzy logic;an improved unscented Kalman filter for maneuvering target tracking;path planning of mobile robot based on genetic-ant colony algorithm;design and implementation of intelligent security robot based on lidar and vision fusion;UAV dynamic obstacle avoidance based on improved reciprocal velocity obstacle;and UAV dynamic obstacle avoidance based on improved reciprocal velocity obstacle.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Question Answering System using NLP and BERT 3

Question Answering System using NLP and BERT

引用

3rd international conference on Smart Electronics and Communication, ICOSEC 2022

作者： Acharya, Shreya Sornalakshmi, K. Paul, Bidisha Singh, Anshul Srm Institute of Science and Technology School of Computing Department of Data Science and Business Systems Tamil Nadu India

ISBN: (数字)9781665497640

ISBN: (纸本)9781665497640

This project proposes a simple and smart question answering system using Named Entity recognition (NER) and Bidirectional Encoder Representations from Transformers (BERT) for communication purposes. Communication is a major factor that eases our day-to-day work. In this smart Question answering system, the system will create a customized dataset for the user based on the answers given by the user. Using NER, only the selective answers are taken, i.e., the most important answers, and then updated in the dataset. Based on that dataset, if a person then asks the system a question, the system will use BERT and CDQA (closed domain question answering) to fetch the best answer for the question asked. The resulting system will be an interactive one. © 2022 IEEE.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Hybrid Deep Learning Cloud Intrusion Detection 3

Hybrid Deep Learning Cloud Intrusion Detection

引用

3rd IEEE international conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Karnan, Lokanayaki Mahalakshmi, S.B. Thirunavukkarasu, V. Christ University Department of Computer Science Karnataka Bangalore560029 India Coimbatore Institute of Technology Department of Artificial Intelligence & Machine Learning Tamil Nadu Coimbatore641014 India

ISBN: (纸本)9798350361186

The scalability and flexibility that cloud computing provides, organisations can readily adapt their resources to meet demand without having to make significant upfront expenditures in hardware infrastructure. Three main types of computing services are provided to people worldwide via the Internet. Increased performance and resource access are two benefits that come with using cloud computing, but there is also an increased chance of attack. As a result of this research, intrusion detection systems that can process massive amounts of data packets, analyse them, and produce reports using knowledge and behaviour analysis were created. Convolution Neural Network Algorithm encrypts data as it's being transmitted end-to-end and is stored in the cloud, providing an extra degree of security. Data protection in the cloud is improved by intrusion detection. This study uses a model to show how data is encrypted and decrypted, of an algorithm and describes the defences against attacks. When assessing the performance of the suggested system, it's critical to consider the time and memory needed to encrypt and decrypt big text files. Additionally, the security of the cloud has been investigated and contrasted with various encoding techniques now in use. © 2024 IEEE.

关键词： Intrusion detection

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 << < 112 113 114 115 116 117 118 119 120 121 > >>

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：