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

4,153 篇 会议
38 册 图书
7 篇 期刊文献

馆藏范围

4,198 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,774 篇 工学
- 2,496 篇 计算机科学与技术...
- 2,042 篇 软件工程
- 615 篇 生物工程
- 614 篇 信息与通信工程
- 364 篇 生物医学工程（可授...
- 295 篇 控制科学与工程
- 223 篇 电气工程
- 211 篇 光学工程
- 161 篇 安全科学与工程
- 142 篇 机械工程
- 129 篇 电子科学与技术（可...
- 120 篇 交通运输工程
- 119 篇 化学工程与技术
- 97 篇 动力工程及工程热...
1,369 篇 理学
- 674 篇 数学
- 645 篇 生物学
- 331 篇 统计学（可授理学、...
- 308 篇 物理学
- 197 篇 系统科学
- 128 篇 化学
748 篇 管理学
- 421 篇 管理科学与工程(可...
- 414 篇 图书情报与档案管...
- 250 篇 工商管理
343 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...
- 126 篇 公共卫生与预防医...
160 篇 法学
- 139 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
6 篇 文学

主题

532 篇 machine learning
248 篇 deep learning
117 篇 support vector m...
99 篇 adversarial mach...
93 篇 accuracy
93 篇 machine learning...
83 篇 forecasting
76 篇 convolutional ne...
70 篇 predictive model...
70 篇 feature extracti...
59 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

2,394 篇 英文
1,803 篇 其他
126 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 4198 条记录，以下是1681-1690 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：

Next-Gen Cucurbit Disease Diagnosis: A Federated learning CNN Approach 12

Next-Gen Cucurbit Disease Diagnosis: A Federated Learning CN...

引用

12th international conference on System Modeling and Advancement in Research Trends, SMART 2023

作者： Suryavanshi, Ankita Kukreja, Vinay Srivastava, Prateek Mehta, Shiva thapliyal, Siddhant Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Computer Science and Engineering Graphic Era Hill University Uttarakhand Dehradun India Computer Science and Engineering Graphic Era Deemed to Be University Uttarakhand Dehradun248002 India

ISBN: (纸本)9798350369861

this study adopts a novel strategy using federated learning with a Convolutional Neural Network (CNN) to identify and categorise Cucurbit leaf diseases. the research includes information from six customers, each with access to distinctive, local datasets of Cucurbit leaf illnesses divided into four severity categories, ranging from 1% to 25% to 50% to 75% to 100%. the use of federated averaging, which combines local model updates into a global one, is a crucial component of this work. this approach highlights a significant development in machine learning by using dispersed data without data centralization. the findings show that the model performed well, with accuracy, recall, and F1-scores ranging from 85.93% to 94.85% across all customers, illuminating the model's strength and adaptability. the performance of the client model Cltt-3 was outstanding, with measures averaging a startling 95%. Additionally, findings from macro, micro, and weighted averages were similarly exceptional, demonstrating the model's adaptability to various class distributions and severity levels. In summary, this work shows the impressive effectiveness of federated learning with CNN in combating Cucurbit leaf diseases and sketches out possible application scenarios. the reliable findings confirm the efficacy of federated learning in a decentralized data environment while opening up fresh opportunities for the global model to be improved using lessons from local datasets. © 2023 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Innovative Deep learning Model-based Stock Price Prediction using a Hybrid Approach of CNN and Gradient Recurrent Unit 8

Innovative Deep Learning Model-based Stock Price Prediction ...

引用

8th international conference on Communication and Electronics Systems, ICCES 2023

作者： Rao, B. Srinivasa Bhattacharya, Rajib Tiwari, Manoj Kumar Kumari, K. Aruna Devmane, Mahavir A. Singh, Kamlesh Gokaraju Rangaraju Institute of Engineering and Technology Department of Computer Science and Engineering Telangana Hyderabad India Globsyn Business School Department of Pgdm Bishnupur JL No. 101 South 24 Paganas West Bengal Chandipur India Jecrc University Department of Computer Application Rajasthan Jaipur India University Mathematics Gss Visakhapatnam India Vppcoe & Va Department of Computer Engineering Maharashtra Mumbai India Graphic Era Hill University Department of Computer Science and Engineering Dehradun India

ISBN: (纸本)9798350396638

the fluctuation in stock prices from industry to industry are a major source of concern in the market. As the market attracts more participants and stock prices play a larger role in more transactions, the ability to accurately predict stock price movements becomes more valuable. When making an investment, many people first look at the share price and then try to anticipate whether or not that price will go up or down in the future. the traditional problem of forecasting the stock market using machine learning tools and methodologies has been thoroughly studied. Time dependence, volatility, and similar complicated dependencies are interesting aspects that make this modeling non-trivial. To overcome this the proposed method in this work is a deep learning-based hybrid strategy for predicting stock prices. Preprocessing is performed after input is delivered to increase precision. Selecting MPSOA features is the next step. In the end, it's put to use in MC-GRU model training. the proposed method achieves better results than both the CNN and GRU models. © 2023 IEEE.

关键词： Investments

来源：评论

学校读者我要写书评

暂无评论

Monitoring and Predicting Performance of Students in Degree Programs using machine learning 10

Monitoring and Predicting Performance of Students in Degree ...

引用

17th INDIACom;2023 10th international conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Kumar, G. Saravana De La Cruz-Camaco, Dante Ravichand, M. Joshi, Kapil Gupta, Zatin Gupta, Sakshi University Karnataka Bengaluru India Universidad Tecnológica Del Perú Peru School of Liberal Arts and Allied Sciences Mohan Babu University India Uttaranchal Institute of Technology Uttaranchal University India School of Computing Science and Engineering Galgotias University Uttar Pradesh Greater Noida India Graphic Era Deemed to Be University Department of Professional Communication Uttarakhand Dehradun248002 India

ISBN: (纸本)9789380544472

In higher education, it is frequently necessary to find a solution to the issue of student retention. Managers and scholars in the field frequently rely entirely and expertise to recognise potential risk factors and students. this study looks at the research on the approaches and metrics being used now in learning analytics. While there are techniques available, our research shows that they are not focused on identifying difficult pupils as soon as possible. With the use of contemporary computer vision tools and methodologies, we design a novel statistical tool for class participation and develop a predictive model. It shows how pupils may be identified with 97% accuracy as early about week three. Additionally, we place this finding in a suitable pedagogical framework to support its application as a component of a more complete student assistance system. there is a wealth of publicly available learning data that can be utilised to analyse individual student behaviour, address their issues, improve the instructional climate, and enable data-driven choices, thanks to the support of software learning platforms. Based on that, the paper focuses on developing a system that can effectively monitor and predict the performance of students in degree programs by using the evolving machine learning. As retention of students has becoming a serious concern, it was necessary to develop performance monitoring and predicting system. Using a comprehensive research methodology this study has analysed all relevant information to the topic to draw an effective conclusion at the end. © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

PE-FedAvg: A Privacy-Enhanced Federated learning for Distributed Android Malware Detection 21

PE-FedAvg: A Privacy-Enhanced Federated Learning for Distrib...

引用

21st IEEE international Symposium on Parallel and Distributed Processing with applications, 13th IEEE international conference on Big Data and Cloud Computing, 16th IEEE international conference on Social Computing and Networking and 13th international conference on Sustainable Computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Tang, Junwei Xu, Zilong Ye, Luyao Peng, Tao He, Ruhan Hu, Xinrong Tian, Wenlong Wuhan Textile University Hubei Provincial Engineering Research Center for Intelligent Textile and Fashion China Wuhan Textile University School of Computer Science and Artificial Intelligence China University of South China School of Computer Science China Nanyang Technological University School of Physical and Mathematical Sciences Singapore

ISBN: (纸本)9798350329223

Android malware detection has become research hotspot in mobile security. When security service providers obtain feature information from target samples, they may involve user privacy information such as identity and behavioral habits, creating an urgent need for a distributed machine learning model to carry out malicious application detection with privacy protection. However, the information exchange between clients and servers in basic federated learning still poses risks of model data leakage, and the likelihood of inferring privacy information from the original feature data is high. therefore, this paper propose a privacy-enhanced federated learning system called PE-FedAvg for distributed Android malware detection. Firstly, Gaussian noise is added to the feature data uploaded from the client to the server, satisfying differential privacy characteristics while retaining data distribution for privacy protection. Secondly, an improved homomorphic encryption algorithm based on modular repeated squaring is used to encrypt and transmit the gradient weight information exchanged between federated learning clients and servers, preventing model-targeted attacks. By conducting the experiments on the Drebin and Malgenome datasets, our design has demonstrated exceptional performance compared to the state-of-the-art work, achieving accuracy rates of 98.61% and 99.3%, respectively. this achievement highlights that our approach not only enhances the security of the federated learning system, but also more effectively accomplishes the detection of Android malware. © 2023 IEEE.

关键词： Android malware

来源：评论

学校读者我要写书评

暂无评论

Production quality early warning method for firearms components based on cloud edge collaboration 4

Production quality early warning method for firearms compone...

引用

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

作者： Sun, Jiawei Hao, Jia Zhang, Xiaoning School of Mechanical Engineering Beijing Institute of Technology Beijing10081 China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing314019 China Key Laboratory of Industry Knowledge and Data Fusion Technology and Application Ministry of Industry and Information Technology Beijing Institute of Technology Beijing10008 China Tianjin Key Laboratory of Space Environment Simulation Technology Tianjing300450 China

ISBN: (纸本)9798400709449

Digital transformation in manufacturing has become a trend with the continuous development of cloud computing and edge computing. the production process of firearms components is highly challenging and quality problems in the production process may directly affect the safety of people's lives and property. thus, this paper proposes a production-quality early warning method for firearms components based on cloud-edge collaboration. Real-time early warning and rapid processing for abnormal conditions in the production process are realized based on cloud data analysis and edge intelligent prediction, thereby improving production efficiency and quality. the cloud edge collaboration framework is developed for cloud training of the long short-term memory models and real-time sample edge acquisition, enhancing the adaptability of quality early warning algorithms under specific conditions and the real-time quality of early warning for firearms components. © 2023 ACM.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

Classification of Ethnic Dress Based on ResNet 4

Classification of Ethnic Dress Based on ResNet

引用

4th international conference on Advances in Electrical Engineering and computer applications, AEECA 2023

作者： Fang, Yangyang Zhang, Jie Fang, Jiemin Southwest Minzu University College of Electronic Information Sichuan Province Chengdu China Fujian Jiangxia University College of Electronic Information Science Fujian Province Fuzhou China

ISBN: (纸本)9798350308082

Deep learning is widely used to process picture information. Chinese ethnic culture is colorful, and ethnic costume is one of the most symbolic representatives. In order to solve the problem of time-consuming and laborious manual classification, this paper uses transfer learning to put forward a method of ethnic costume classification based on ResNet. the convolution neural network is used to extract the features of different ethnic costumes to realize the classification. In the experiment, we first used ResNet, AlexNet, LeNet and GoogLeNet for training, and found that ResNet had the best effect, but the initial recognition accuracy was not high, the primary reason was insufficient data, so we first expanded the data set, and established a national costume data set with about 10,000 pictures. 70% of them are used as the training set and 30% as the test set. After image preprocessing, it is cut to the size of 300∗300∗3. the learning rate decay strategy is then introduced along with a deeper ResNet network - ResNext that is stacked from Inception modules. the final experimental results show that the recognition accuracy of ResNet18 is the highest, and its accuracy rate, recall rate and f1-score are about 0.6. this experiment lays a good foundation for the information processing of national costumes, and also provides support for the inheritance and protection of national culture. © 2023 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Deep learning for speech emotion recognition: A technical tutorial on the state of the art 8

Deep learning for speech emotion recognition: A technical tu...

引用

8th international conference on Information Systems Engineering, ICISE 2023

作者： Liu, Hai Li, Jiawen Zhao, Li Si, Junya Li, Weixin Shen, Dazhen Li, Zixin Liu, Tingting Wuhan Donghu University School of Computer Science Wuhan430212 China

ISBN: (纸本)9798350307009

Speech is the simplest, most natural and most direct way of communication between people, and the rise of smart devices makes speech emotion recognition (SER) technology the most important part of human-computer interaction (HCI). this paper will start from the concept of language emotion recognition, and research the systematic research on speech emotion recognition in five aspects. First, we review the classification of some phonetic emotional features. Secondly, we introduce some of the latest technologies for speech emotion recognition based on traditional and machine learning. Furthermore, we summarize the classification of some common datasets. Finally, we discuss the practical application and future research direction of speech emotion recognition. © 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

Multi-Objective and Multiple Information Source Optimization for Fair & Green machine learning 4th

Multi-Objective and Multiple Information Source Optimizatio...

引用

4th international conference on Numerical Computations: theory and Algorithms, NUMTA 2023

作者： Candelieri, Antonio Ponti, Andrea Archetti, Francesco University of Milano-Bicocca Milan20126 Italy

ISBN: (纸本)9783031812408

Democratizing machine learning (ML) requires endowing ML algorithms with fairness and low environmental impact. Training ML models on real-life data might lead to inherently biased predictions, a critical issue when the bias translates into discrimination of certain social groups. this unfairness is exacerbated by searching for the best predictive model only depending on accuracy. FairML was initially addressed as a constrained optimization problem, but recently multi-objective methods proved to be more effective. the second issue, considered here, is the carbon footprint of ML: the massive usage of computational resources for training ML models, and searching for the best one, implies a significant environment impact, leading to Green AutoML methods. Recent approaches estimate the carbon footprint as a proxy of the energy consumption and reduce it by using multiple information sources (i.e., small portions of the data), each with a different fidelity and cost. We propose a method combining multi-objective and multiple information source into a single Bayesian optimization framework. It was evaluated on four fairness datasets and three ML algorithms, and compared those from state-of-the-art methods. Results empirically prove that our method outperforms the others in terms of accuracy, fairness, and "greenness". © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Zero-carbon

来源：评论

学校读者我要写书评

暂无评论

A Simple User-friendly Android application for Oxygen and Blood Pressure Measurement 4

A Simple User-friendly Android Application for Oxygen and Bl...

引用

4th international conference on Cybernetics, Cognition and machine learning applications, ICCCMLA 2022

作者： Cheemakurthi, Srujan Chakka, Jahnavi Parida, Sagar Mousam Praneeth, V.N. Siva Kinjal Debasis, Kumar VIT-AP University School of Computer Science and Engineering Amaravati India VIT-AP University School of Electronics Engineering Amaravati India

ISBN: (数字)9781665462464

ISBN: (纸本)9781665462464

In the current generation, health is a major concern for people regardless of age. People were so drastically affected by the pandemic that they couldn't muster up the courage to visit a hospital for a general checkup. Monitoring one's health condition is vital, especially for senior citizens. Photo-plethysmography is an optical measurement method used to compute the arterial blood volumetric variations of blood circulation with the help of a pulse oximeter. A pulse oximeter uses a bright LED at one end and a detector on the other end to measure the pulse rate and oxygen saturation. Hypoxemia is one of the common issues faced in recent times which is caused by the dropping of oxygen levels. It causes frequent headaches, dysfunction of the brain, heart, etc. Hence, there exists a necessity for a device that can monitor a person's oxygen levels and provide a rough estimate. this paper proposes an android application that can provide an estimate of a person's oxygen levels with over 90% accuracy. the application also predicts the rough value of blood pressure. © 2022 IEEE.

关键词： Blood pressure

来源：评论

学校读者我要写书评

暂无评论

FoodSavior: Distributing Surplus Food to NGOs or Manure Producers Using Internet of things and machine learning 5

FoodSavior: Distributing Surplus Food to NGOs or Manure Prod...

引用

5th international conference on Sustainable Communication Networks and application, ICSCNA 2024

作者： Uke, Shailaja Jadhav, Prithviraj Kakarwal, Urmila Kolawale, Sanika Nikam, Vivek Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798331530013

By evaluating the quality of leftover food and enabling its best possible redistribution, this research presents a novel approach to addressing food waste in the restaurant sector. the system uses a Flutter an Dart-based application to control the food distribution process and hardware sensors like MQ4 to identify gasses that indicate spoiling. While spoiled food is sent to manure producers for use in agriculture, non-spoiled food is sent to NGOs to feed people in need. In order to minimize waste, the system analyzes sensor data and uses machine learning algorithms, such as Decision Trees, to forecast spoiling patterns and suggest preparation techniques. Restaurants can quickly enter food data into the app, which NGOs and manure producers may use to collaborate in real time. this data is processed by the Django-developed backend server, and Arduino C++ is used to control hardware activities. this solution promotes sustainability, social responsibility, and community welfare by facilitating a smooth collaboration between farmers, restaurants, and non-governmental organizations. the method helps create a more sustainable and just food environment by decreasing food waste and improving resource efficiency. this version emphasizes the objectives, innovation, and societal impact of the work while maintaining technical details. © 2024 IEEE.

关键词： C++ (programming language)

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420页 << < 165 166 167 168 169 170 171 172 173 174 > >>

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：