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

4,137 篇 会议
38 册 图书
6 篇 期刊文献

馆藏范围

4,181 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,738 篇 工学
- 2,465 篇 计算机科学与技术...
- 2,042 篇 软件工程
- 616 篇 生物工程
- 587 篇 信息与通信工程
- 362 篇 生物医学工程（可授...
- 266 篇 控制科学与工程
- 216 篇 电气工程
- 211 篇 光学工程
- 148 篇 安全科学与工程
- 136 篇 机械工程
- 124 篇 电子科学与技术（可...
- 118 篇 化学工程与技术
- 107 篇 交通运输工程
- 91 篇 动力工程及工程热...
1,369 篇 理学
- 675 篇 数学
- 646 篇 生物学
- 332 篇 统计学（可授理学、...
- 307 篇 物理学
- 197 篇 系统科学
- 127 篇 化学
720 篇 管理学
- 393 篇 管理科学与工程(可...
- 388 篇 图书情报与档案管...
- 237 篇 工商管理
340 篇 医学
- 315 篇 临床医学
- 308 篇 基础医学(可授医学...
- 221 篇 药学(可授医学、理...
- 125 篇 公共卫生与预防医...
159 篇 法学
- 138 篇 社会学
157 篇 教育学
- 155 篇 教育学
141 篇 农学
- 140 篇 作物学
89 篇 经济学
9 篇 军事学
5 篇 文学

主题

526 篇 machine learning
243 篇 deep learning
117 篇 support vector m...
99 篇 adversarial mach...
92 篇 accuracy
92 篇 machine learning...
83 篇 forecasting
75 篇 convolutional ne...
70 篇 predictive model...
69 篇 feature extracti...
58 篇 artificial intel...
53 篇 students
51 篇 learning systems
48 篇 decision trees
48 篇 training
47 篇 reinforcement le...
47 篇 computational mo...
47 篇 computer vision
46 篇 internet of thin...
41 篇 neural networks

机构

46 篇 chitkara univers...
15 篇 graphic era hill...
10 篇 college of manag...
9 篇 graphic era deem...
8 篇 computer science...
8 篇 beijing universi...
7 篇 school of comput...
7 篇 school of comput...
7 篇 school of comput...
7 篇 department of in...
6 篇 università di ca...
6 篇 infn sezione di ...
6 篇 north-west unive...
6 篇 computer science...
6 篇 lovely professio...
6 篇 in2p3 lpc campus...
6 篇 kkr and ksr inst...
6 篇 institut univers...
6 篇 national centre ...
6 篇 greater bay area...

作者

18 篇 kukreja vinay
15 篇 mehta shiva
10 篇 william p.
8 篇 sharma vikrant
7 篇 mahamudul hasan
7 篇 shiva mehta
6 篇 chen a.
6 篇 benoit d.m.
6 篇 ferrara g.
6 篇 ardid m.
6 篇 calvo d.
6 篇 gagliardini s.
6 篇 eddymaoui a.
6 篇 kulikovskiy v.
6 篇 labalme m.
6 篇 gal t.
6 篇 bozza c.
6 篇 khatun a.
6 篇 kalekin o.
6 篇 huang f.

语言

3,930 篇 英文
250 篇 其他
34 篇 中文

检索条件"任意字段=Proceedings of the 2023 4th International Conference on Machine Learning and Computer Application"

共 4181 条记录，以下是1071-1080 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：

Leveraging machine learning for Comprehensive Analysis of Maternal Health: Predicting Health Risks and Improving Antenatal Care 4th

Leveraging Machine Learning for Comprehensive Analysis of Ma...

引用

4th international conference on Mobile Radio Communications and 5G Networks, MRCN 2023

作者： Tiwari, Raj Gaurang Agarwal, Ambuj Kumar Jain, Vishal Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Department of Computer Science and Engineering School of Engineering and Technology Sharda University Greater Noida India

ISBN: (纸本)9789819706990

the health of the mother is crucial to the well-being of the baby throughout pregnancy. Early treatments and individualized care may be more effective when maternal health hazards are properly classified. In this study, we explore the feasibility of using fundamental and boosting machine learning algorithms to categorize threats to maternal health. On an extensive collection of maternal health indicator variables, we test the efficacy of many machine learning techniques, including logistic regression, decision trees, random forest, gradient boosting, and XGBoost. With an experimental accuracy in classification of 86.48%, our data show that XGBoost performs well. To further verify XGBoost’s efficacy, we use several assessment criteria, such as the lift curve and the ROC curve. these results provide important insight into how machine learning might be used to enhance prenatal care and lessen associated hazards to mothers. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Health risks

来源：评论

学校读者我要写书评

暂无评论

Comparison of CNN models for picture description application 4

Comparison of CNN models for picture description application

引用

4th international conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022

作者： Srivastava, Ayushi Meena, Isha Manisha, K. Bansal, Ankita Nsut Department of It New Delhi India

ISBN: (纸本)9781665474368

Blindness makes life tough for those who suffer from it, but machine learning can assist the visually impaired with their day - to - day tasks. Presently, image to speech is a relatively new and naïve topic. It's a machine learning problem that requires both natural language processing and computer vision to analyze visual content. In this context, this work focuses on the development of a photo-to-speech application for the visually impaired people. the work's ideology aims to make an impact on society so that visually impaired people can achieve equality. We merged picture and text processing in this work to build a practical deep learning application. © 2022 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Homomorphic Encryption based Federated learning for Financial Data Security 4

Homomorphic Encryption based Federated Learning for Financia...

引用

4th international conference on Computing and Communication Systems, I3CS 2023

作者： Dhiman, Shalini Nayak, Sumitra Mahato, Ganesh Kumar Ram, Anil Chakraborty, Swarnendu Kumar National Institute of Technology Department of Computer Science & Engineering Arunachal Pradesh India

ISBN: (纸本)9798350323771

Federated learning is a distributed machine learning technique that enables on-device training without exchanging the sensitive data over the centralized server. In this paper, Federated learning is used to train financial data models on-devices with the help of IoT applications in financial or business systems. this creates more advanced and secured financial business models. We have applied the mechanism of homomorphic encryption and cryptographic primitives, including masking and local model protection to prevent any kind of inferring in private financial or business data where multiple attackers usually find a way of model inversion or reconstruction attack. We used datasets of various financial sectors as the primary measure, rather than taking the size of datasets that is generally used in deep learning, to get the correct measurement of the rate of contribution in every session of the local model's training to the training of the global model. If the calculated online number of clients exceeds a predetermined threshold, then the federated learning process will be continued with the dropout-tolerant plan. the security study demonstrates that the suggested solution fulfils data privacy requirements. the costs of computation and communication are also examined theoretically. According to research observations, the proposed approach achieved promising outcomes while assuring privacy preservation when compared to existing schemes. © 2023 IEEE.

关键词： Sensitive data

来源：评论

学校读者我要写书评

暂无评论

proceedings of the 6th ACM conference on Fairness, Accountability, and Transparency, FAccT 2023

Proceedings of the 6th ACM Conference on Fairness, Accountab...

引用

6th ACM conference on Fairness, Accountability, and Transparency, FAccT 2023

ISBN: (纸本)9781450372527

the proceedings contain 144 papers. the topics discussed include: machine explanations and human understanding;broadening AI ethics narratives: an Indic art view;how to explain and justify almost any decision: potential pitfalls for accountability in AI decision-making;‘we are adults and deserve control of our phones’: examining the risks and opportunities of a right to repair for mobile apps;fairness in machine learning from the perspective of sociology of statistics: how machine learning is becoming scientific by turning its back on metrological realism;two reasons for subjecting medical AI systems to lower standards than humans;optimization’s neglected normative commitments;humans, AI, and context: understanding end-users’ trust in a real-world computer vision application;multi-dimensional discrimination in law and machine learning – a comparative overview;reconciling individual probability forecasts;the gradient of generative AI release: methods and considerations;and in the name of fairness: assessing the bias in clinical record de-identification.

关键词：

来源：评论

学校读者我要写书评

暂无评论

4th international conference on Computing and Data Science

4th International Conference on Computing and Data Science

引用

4th international conference on Computing and Data Science, CONF-CDS 2022

the proceedings contain 32 papers. the topics discussed include: intelligent path planning of mobile robot based on genetic algorithm;accuracy improvement based on classic neural network: voting, restarting and quantization;two applications of manifold regularization in deep learning architectures;an automatic wound detection system empowered by deep learning;data generation using simulation technology to improve perception mechanism of autonomous vehicles;detection of ischemic brain stroke using deep learning;self-supervised approach to addressing zero-shot learning problem;fault diagnosis of high-speed railway turnout system based on improved group decision-making;machine learning and deep learning methods on breast cancer metastases detection;turnout failure diagnosis system based on group decision making strategy;and improved causal Bayesian optimization algorithm with counter-noise acquisition function and supervised prior estimation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Review on Radiomics and machine learning Algorithms in Prediction and Progression of Parkinson's Disease 4

A Review on Radiomics and Machine Learning Algorithms in Pre...

引用

4th international conference on Advances in Computing, Communication Control and Networking, ICAC3N 2022

作者： Redhya, M. Kumar, K. Sathesh Kalasalingam Academy of Research and Education Department of Computer Applications Tamil Nadu Krishnankoil India Kalasalingam Academy of Research and Education Department of Computer Science and Information Technology Tamil Nadu Krishnankoil India

ISBN: (纸本)9781665474368

Parkinson's disease (PD) is an irreversible neurodegenerative condition that impairs dopamine production in a specific area of the brain. Diagnosis of PD in the early stage is a tedious task as symptoms are not very prominently shown in the first stage. machine learning techniques had been used for the analysis and progression of PD. Radiomics analysis has helped in extracting large amount of quantifiable features from images which can be used as biomarkers for predictive models. this paper gives an idea on different machine learning algorithms and the application of radiomics which has proven its efficacy in the classification and progression of PD. Finally, the limitations and accuracy of the different techniques are also discussed. © 2022 IEEE.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

Research on Interactive Advertising Strategies Using machine learning Algorithms for User Behavior Analysis 4

Research on Interactive Advertising Strategies Using Machine...

引用

4th international conference on Big Data Economy and Information Management, BDEIM 2023

作者： Liu, Jiaquan Yang, Haijun School of journalism & communication Shanghai University China

ISBN: (纸本)9798400716669

Based on the collection of user behavior logs and multi-source feature representation, this study integrates convolutional neural networks and recurrent neural networks to establish deep learning models, achieving accurate mining of personalized user interests and constructing high-quality user profiles. On this basis, a dynamic advertising strategy generation mechanism based on reinforcement learning is introduced, relying on user feature states to achieve precise targeting and dynamic optimization adjustments, resulting in higher conversion levels. Simulation environment test results show that compared to traditional techniques, the constructed personalized reinforcement learning advertising matching system has made significant progress in user profile extraction and decision tuning. Empirical evidence from a video website user log case further validates the effectiveness of the method. this research explores for the first time the innovative integration of deep learning and reinforcement learning technologies in the field of interactive advertising, providing theoretical and technical support for solving the challenge of personalized precision recommendations and significantly improving the level of related systems, with broad application prospects. © 2023 ACM.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

machine learning in Warehouse Management: A Survey 5

Machine Learning in Warehouse Management: A Survey

引用

5th international conference on Industry 4.0 and Smart Manufacturing (ISM)

作者： de Assis, Rodrigo Furlan Faria, Alexandre Frias thomasset-Laperriere, Vincent Sanata-Eulalia, Luis Antonio Ouhimmou, PaulaMustapha Ferreira, William de Paula Ecole Technol Super Dept Syst Engn Montreal PQ H3C 1K3 Canada Univ Sherbrooke Business Sch Sherbrooke PQ J1K 2R1 Canada Product Quebec Sherbrooke PQ J1G 4L3 Canada

Warehouse design and planning involve complex decisions on receiving, storage, order picking and shipping products (ie., stock- keeping units - SKUs) and can affect the performance of entire supply chains. With the advancement of Industry 4.0 and increased data availability, high-computing power, and ample storage capacity, machine learning (ML) has become an appealing technology to address warehouse planning challenges such as Storage Location Assignment Problems (SLAP) and Order Picking Problems (OPP) for intelligent warehousing management. this paper presents a state-of-the-art review of ML applied to Warehouse Management Systems (WMS) through the analysis of recent research application articles. A mapping to classify the scientific literature in this new research area, including ML methods, algorithms, data sources and use cases of ML-aided WMS, as well as further research perspectives and challenges, are introduced. Preliminary results suggest that the possible research areas in ML-WMS are still incipient and need to be further explored.

关键词： Industry 4.0 Artificial Intelligence Order Picking Storage Location Assignment

来源：评论

学校读者我要写书评

暂无评论

Assessing the Performance of PINN and CNN Approaches in Solving the 1D Burgers' Equation with Deep learning Architectures 4

Assessing the Performance of PINN and CNN Approaches in Solv...

引用

4th international conference on machine learning and computer application, ICMLCA 2023

作者： Li, Cheng School of Computer Science and Engineering Faculty of Innovation Engineering Macau University of Science and Technology Macau999078 China

ISBN: (纸本)9798400709449

Deep learning has emerged as a promising approach for solving complex partial differential equations (PDEs) using data-driven methods, particularly in scenarios where traditional numerical techniques face limitations. the 1D Burgers' Equation, which combines convection and diffusion terms, is a fundamental PDE used to model various physical phenomena, including fluid dynamics and shock waves. While analytical solutions for this equation are challenging due to its nonlinearity, specific cases do have exact solutions. this research systematically evaluates the effectiveness of two popular deep learning methodologies, Physics-Informed Neural Networks (PINNs) and Convolutional Neural Networks (CNNs), in solving the 1D Burgers' Equation. A particular focus of the assessment is to explore potential bias in the training dataset. the neural networks are trained using biased samples, and their results are rigorously compared with those obtained from unbiased samples. this investigation provides insights into the performance of these deep learning architectures and their sensitivity to the quality of training data. the research reveals significant sample bias effects on neural network (NN) models. Primitive bias notably impacts Convolutional Neural Networks (CNNs) more than Physics-Informed Neural Networks (PINNs). this is attributed to differences in loss function calculation, making bias selection more straightforward for CNNs. © 2023 Owner/Author.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

machine learning Applied to Speech Recordings for Parkinson's Disease Recognition 1

引用

4th international conference on Deep learning theory and applications (DeLTA)

作者： Aversano, Lerina Bernardi, Mario L. Cimitile, Marta Iammarino, Martina Madau, Antonella Verdone, Chiara Univ Sannio Dept Engn Benevento Italy Unitelma Sapienza Univ Rome Italy

ISBN: (数字)9783031390593

ISBN: (纸本)9783031390586;9783031390593

Parkinson's disease is a common neurological condition that occurs when dopamine production in the brain decreases significantly due to the degeneration of neurons in an area called the substantia nigra. One of its characteristics is the slow and gradual onset of symptoms, which are varied and include tremors at rest, rigidity, and slow speech. Voice changes are very common among patients, so analysis of voice recordings could be a valuable tool for early diagnosis of the disease. this study proposes an approach that compares different machine learning models for the diagnosis of the disease through the use of vocal recordings of the vowel a made by both healthy and sick patients and the identification of the subset of the most significant features the experiments were conducted on a data set available on the UCI repository, which collects 756 different recordings. the results obtained are very encouraging, reaching an F-score of 95%, which demonstrates the effectiveness of the proposed approach.

关键词： Parkinsons's disease Speech recordings machine learning Early diagnosis

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419页 << < 104 105 106 107 108 109 110 111 112 113 > >>

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：