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

4,129 篇 会议
38 册 图书
6 篇 期刊文献

馆藏范围

4,173 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

2,733 篇 工学
- 2,463 篇 计算机科学与技术...
- 2,042 篇 软件工程
- 616 篇 生物工程
- 586 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
- 214 篇 电气工程
- 211 篇 光学工程
- 147 篇 安全科学与工程
- 136 篇 机械工程
- 123 篇 电子科学与技术（可...
- 118 篇 化学工程与技术
- 105 篇 交通运输工程
- 91 篇 动力工程及工程热...
1,368 篇 理学
- 674 篇 数学
- 646 篇 生物学
- 332 篇 统计学（可授理学、...
- 306 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
156 篇 教育学
- 154 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

522 篇 machine learning
240 篇 deep learning
117 篇 support vector m...
99 篇 adversarial mach...
92 篇 accuracy
92 篇 machine learning...
83 篇 forecasting
74 篇 convolutional ne...
70 篇 predictive model...
69 篇 feature extracti...
57 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 sentiment analys...

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

4,030 篇 英文
142 篇 其他
30 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 4173 条记录，以下是4091-4100 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：

Adaptive traffic signal control based on Dueling Deep Q-learning Network 22

Adaptive traffic signal control based on Dueling Deep Q-Lear...

引用

proceedings of the 2022 4th international conference on Robotics, Intelligent Control and Artificial Intelligence

作者： Zhuohang Xu Ping Wang Libin Zhang Fan Qi Guiping Wang School of Electronic and Control Engineering Chang45an University China

ISBN: (纸本)9781450398343

the intersection is the place where traffic flow converges and traffic accidents are most likely to occur, and the traffic conditions at intersections is also complex, which is easy to cause congestion and reduce the traffic efficiency. With the development of intelligent transportation system, adaptive traffic signal control is proposed to improve the traffic efficiency of the intersection by adjusting the phase sequence of the signal in real time. Meanwhile, with the extensive application of reinforcement learning in the traffic field, dueling DQN (Deep Q-learning Network) is introduced to realize the adaptive traffic signal control in this paper. By comparing the traffic flow conditions of intersections under different signal control methods, we find that dueling DQN can effectively improve the traffic efficiency of intersections under the condition of random change of traffic flow. through experiment results, we can conclude that the expected reward of dueling DQN is 41.1% and 4.8% higher than that of fixed phase method and DQN method. Meanwhile, simulation result shows that dueling DQN can react to the traffic flow of the road network more timely, and has higher stability than DQN, which can effectively improve the traffic efficiency.

关键词：

来源：评论

学校读者我要写书评

暂无评论

SDPP: A tumor disease diagnosis application based on vibration spectroscopy and machine learning 23

SDPP: A tumor disease diagnosis application based on vibrati...

引用

proceedings of the 2023 4th international Symposium on Artificial Intelligence for Medicine Science

作者： Chenjie Chang Guifeng Zhao Xiaoyi Lv College of Software Xinjiang University China

ISBN: (纸本)9798400708138

Molecular vibrational spectroscopy is an essential technique for analyzing the biomolecular components of human tissues and body fluids with high sensitivity. there are many studies on tumor disease diagnosis that combine artificial intelligence with vibrational spectroscopy, and vibrational spectroscopy has shown good potential in non-invasive disease auxiliary diagnosis. However, the complexity of spectral data processing flow and the variety of algorithms make it difficult for non-professionals to use it efficiently, which limits the development of molecular vibrational spectroscopy-assisted diagnosis technology. this study developed the Spectral Data Processing Platform (SDPP) that normalizes the data processing flow. SDPP can quickly perform preprocessing, feature extraction, and model building on spectral data. As an application desktop program, SDPP has an executable file size of 232 M, an average response time of 3 s for each component, an average CPU utilization rate of 7.30%, and a throughput of 106 times/s. the experimental data selected for testing the platform were collected from Raman data and infrared data of patients and the control group. the results showed that SDPP could efficiently classify patients and the control group and also proved the stability and operability of SDPP.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Prediction of COVID-19 Epidemiology with Chest computerized Tomography Images Using machine learning Techniques

Prediction of COVID-19 Epidemiology with Chest Computerized ...

引用

international Multidisciplinary Information Technology and Engineering conference (IMITEC)

作者： Khokhoni Innocentia Mpho Ramaphosa Tranos Zuva Temidayo Otunniyi Faculty of Applied and Computer Sciences Vaal University of Technology Vanderbijlpark South Africa

ISBN: (数字)9798350387988

ISBN: (纸本)9798350387995

the COVID-19 pandemic placed immense pressure healthcare systems, emphasizing the need for efficient prediction methods. this research proposes a deep learning-based solution using Convolutional Neural Networks (CNNs) to classify chest CT scan images as either COVID-19 positive or negative. A dataset of 400 normal and 399 COVID-19 CT scan images was used to evaluate CNN models, including VGG19, DenseNet201, Xception, InceptionV3, and VGG16, over 25 and 50 epochs. At 25 epochs, DenseNet201 achieved the highest accuracy of 97%, followed by VGG16 at 96%, InceptionV3 at 93%, and VGG19 and Xception at 91%. At 50 epochs, accuracy improved, with VGG16 and DenseNet201 both reaching 98%, and VGG19 at 97%. Xception and Inception V3also saw improvements, reaching 96%. VGG16 consistently achieved 100% for both Precision and Recall across all epochs, while DenseNet201 maintained 100% Precision at 25 epochs but dropped to 95% at 50 epochs. Xception showed significant improvement in Recall, rising from 85% to 97%. Enhanced preprocessing, including noise reduction and contrast adjustment, further boosted model performance. A COVID-19 Prediction Web application (CPWA) was developed using the fine-tuned VGG19 model to offer a practical tool for healthcare professionals. this study demonstrates the potential of AI-driven diagnostics to streamline COVID-19 screening and improve early diagnosis, providing scalable solutions for clinical settings.

关键词： COVID-19 Accuracy Pandemics Computed tomography Noise reduction Medical services machine learning Streaming media Predictive models Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

AI-Enhanced Lung Cancer Detection Using the ResNext50 Architecture

AI-Enhanced Lung Cancer Detection Using the ResNext50 Archit...

引用

Intelligent Technologies (CONIT), international conference on

作者： Om Garg Rishabh Sharma Saumitra Chattopadhyay Aditya Verma Vishal Jain Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Computer Science and Engineering Graphic Era Hill University Dehradun Uttarakhand India Computer Science and Engineering Graphic Era Deemed to be University Dehradun Uttrakhand India Department of Computer Science and Engineering Sharda School of Engineering and Technology Sharda University Greater Noida U.P India

ISBN: (数字)9798350349900

ISBN: (纸本)9798350349917

Lung cancer as the first cause of cancer death among people in many countries shows the necessity of creating a straightforward as well as accurate test for identifying the disease at an early stage. In the last several years automatic learning (AI) of machine learning (ML) technologies have been regarded as great techniques for medical diagnostics with the help of imaging analysis. this article will take the ResNext50 architecture, a variant of convolutional neural networks (CNN), as a model. It will use the ResNext50 architecture as an example of the AI-enhanced lung cancer detection neural network. the methodology has the following steps: obtain a versatile database of CT scans (chest) with labeled cancerous lung lesions. As preprocessing steps, we apply techniques like normalization, resizing, and augmentation for standardization, and the augmentation for enhancement of the dataset. ResNext50 is embraced as the main backbone for the lung cancer detection system being an advantage of transfer learning and fine-tuning, which helps improve the model’s efficiency. We assess the performance of the model according to a set of metrics which estimate the correctness of the model. these include accuracy, sensitivity, specificity, precision, F1-score, and the area under the receiver operating characteristic (AUC-ROC) curve. Competitive evaluations are executed to compare the baseline methods and the superiority of the considered procedure. the results confirm that the ResNext 50 model reached a high level of 92%, with an accurate evaluation of metrics that matter. Performance check of the ResNext50 model versus baseline methods proves this model’s superiority and bringing out more significant advantages while working with advanced CNNs is recommended for lung cancer detection.

关键词： Accuracy Sensitivity Smoothing methods Transfer learning Lung cancer Standardization Robustness

来源：评论

学校读者我要写书评

暂无评论

An Novel Based Mobile Dropping Sesing to Protect using Inertia Sensor and Integration of DL Technology

An Novel Based Mobile Dropping Sesing to Protect using Inert...

引用

Advance Computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： S.R. Barkunan J. Radha Raju Egala Ritesh Kumar Singhal Mohammed Ayad Alkhafaji Ban Sefeer Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi India Department of CSE Nandha Engineering College Perundurai Tamilnadu Department of ECE Gayatri Vidya Parished College for Degree and Pg Courses(A) Visakhapatnam Andhra Pradesh Ajay Kumar Garg Institute of Management Ghaziabad College of Technical Engineering National University of Science and Technology Dhi Qar Iraq Al-Farahidi university Baghdad Iraq

ISBN: (数字)9798350360165

ISBN: (纸本)9798350360172

With all such technologies, the recent advances in health monitoring due to smartphone sensor technologies provide an opportunity to quantify an individual’s functional performance and deviations from normality. Falling and drowning are two major unnatural reasons for accidental silent death, and it requires an ambient approach to detect the same. this paper presents a novel ambient assistive framework, FaDD (Falling and Drowning Detection), designed for identifying and distinguishing incidents of falls or drowning. Input data are taken through smartphone sensors like the accelerometer, gyroscope, magnetometer, and GPS, which capture the movement of a person’s body for effective recognition. By adopting a hierarchical approach, FaDD effectively detects dropping and choking actions using machine learning models. the framework is also integrated with the emergency alert notifications embedded in a smartphone application and, in the case of drowning, immediately alerts the respective stakeholders of the guardians, rescue team, and close community circle. With an accuracy rate of ${9 8 \%}$, FaDD is proficient in detecting falls, drowning, and normal activities. Coordination of all stakeholders through the FaDD framework is bound to enhance the provision of an effective and efficient health service to the people.

关键词： Accelerometers Accuracy Magnetometers Computational modeling machine learning Gyroscopes Stakeholders

来源：评论

学校读者我要写书评

暂无评论

A New Feature Selection Method for Internet Traffic Classification Using ML

A New Feature Selection Method for Internet Traffic Classifi...

引用

2010 4th international conference on Intelligent Information Technology application (IITA2010)

作者： Liu Zhen School of computer science and engineering South China University of Technology Guangzhou, China Liu Qiong School of software South China University of Technology Guangzhou, China

If 248 statistical features are used to characterize network traffic flows, the computation cost of classifier will be overlarge. the feature selection methods referenced here improve the accuracy of majority classes and meanwhile decrease the accuracy in minority classes as the cost. As a result, it brings about the multi-class imbalance problem. In this paper, main contributions include two aspects below. 1) An evaluation criterion based on information theory was proposed to assess how much do one feature bias towards one class. 2) A new feature selection method named BFS was proposed to reduce features and alleviate multi-class imbalance. BFS was compared with fast correlation-based filter (FCBF) and full feature set using Nave Bayes and ten skewed datasets. the results show that 1) BFS is more advantage to maintain the balance of multi-class classification results than FCBF, such as the reduction of g-mean is just about 8% using BFS, 2) classification accuracy of Nave Bayes using BFS can achieve to 90%.

关键词： machine learning feature selection multiclass imbalance Internet traffic classification

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Federated learning with Gaussian Differential Privacy 22

Hierarchical Federated Learning with Gaussian Differential P...

引用

proceedings of the 4th international conference on Advanced Information Science and System

作者： Tao Zhou China Telecom Cybersecurity Technology Co. Ltd China

ISBN: (纸本)9781450397933

Federated learning is a privacy preserving machine learning technology. Each participant can build the model without disclosing the underlying data, and only shares the weight update and gradient information of the model with the server. However, a lot of work shows that the attackers can easily obtain the client’s contributions and the relevant privacy training data from the public shared gradient, so the gradient exchange is no longer safe. In order to ensure the security of Federated learning, in the differential privacy method, noise is added to the model update to obscure the contribution of the client, thereby resisting member reasoning attacks, preventing malicious clients from knowing other client information, and ensuring private output. this paper proposes a new differential privacy aggregation scheme, which adopts a more fine-grained hierarchy update strategy. For the first time, the f-differential privacy (f-DP) method is used for the privacy analysis of federated aggregation. Adding Gaussian noise disturbance model update in order to protect the privacy of the client level. We prove that the f-DP differential privacy method improves the previous privacy analysis by experiments. It accurately captures the loss of privacy at every communication round in federal training, and overcome the problem of ensuring privacy at the cost of reducing model utility in most previous work. At the same time, it provides a federal model updating scheme with wider applicability and better utility. When enough users participate in federated learning, the client-level privacy guarantee is achieved while minimizing model loss.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

9th international conference on Computing and Informatics, ICOCI 2023

9th International Conference on Computing and Informatics, I...

引用

9th international conference on Computing and Informatics, ICOCI 2023

ISBN: (纸本)9789819995882

the proceedings contain 55 papers. the special focus in this conference is on Computing and Informatics. the topics include: Sentiment Analysis of Arabic Dialects: A Review Study;charting Inclusive Digital Society Research Trends: A Bibliometric Analysis of E-Participation through Social Media;systematic Literature Review and Bibliometric Analysis on Addressing the Vanishing Gradient Issue in Deep Neural Networks for Text Data;a Test Dataset of Offensive Malay Language by a Cyberbullying Detection Model on Instagram Using Support Vector machine;tikTok Video Cluster Analysis Based on Trending Topic;a Video Summarization Method for Movie Trailer-Genre Classification Based on Emotion Analysis;e-Nose: Spoiled Food Detection Embedded Device Using machine learning for Food Safety application;an Analysis of Objective Function Modification Approaches in Routing Protocols for Low Power and Lossy Networks: A Fuzzy Logic-Based Perspective;an Empirical Study of Label Size Effect on Classification Model Accuracy Using a Derived Rule from the Holy Quran Verses;large Scale Web Crawling and Distributed Search Engines: Techniques, Challenges, Current Trends, and Future Prospects;anomalies in Mooring (thin) Lines: Causes, Risk Mitigations, and Real Time Consequences of Failure – A Comprehensive Review;data Analytics Modelling System for Short Courses at Seberang Jaya Community College;examining the Software Developers’ Perception in Open-Source Software of Blockchain Project Using Association Rules Mining;support Vector machine for Satellite Images Classification Using Radial Basis Function Kernel Method;a Regression Test Case Prioritization Framework for Software Sustainability;towards a Sustainable Digital Society: Supporting Producer Mobility in Named Data Networking through Immobile Anchor-Based Mechanism.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards Eco-Resilient Networks: CNN-Enabled Anomaly Detection for Green Cybersecurity

Towards Eco-Resilient Networks: CNN-Enabled Anomaly Detectio...

引用

Advancement in Electronics & Communication Engineering (AECE), international conference on

作者： Arman Kalra Kanwarpartap Singh Gill Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (数字)9798350364729

ISBN: (纸本)9798350364736

Cybersecurity is a major concern across various industries today. It is directly related to global goals such as enhancing infrastructure and industrial innovation (SDG 9) and fostering peace, justice, and strong institutions (SDG 16). Traditional problem-detection methods are becoming less effective as cyber threats evolve and increase in frequency, necessitating new approaches. this article introduces a novel technique for detecting abnormal patterns in network traffic using Convolutional Neural Networks (CNNs). the model is trained and tested on the CICIDS2017 dataset, which includes a wide range of both normal and suspicious network activities. Our CNN-based approach achieved a remarkable accuracy of 93.64%, outperforming conventional techniques. this method not only enhances cybersecurity but also contributes to SDG 9 by promoting resilient infrastructure. Additionally, it aids in building robust institutions by swiftly detecting and mitigating cyber threats, aligning with SDG 16. the performance of the model, including metrics like accuracy, recall, F1 score, and confusion matrices, has been thoroughly analyzed. these results underscore the importance of leveraging advanced machine learning techniques, especially deep learning, in cybersecurity solutions. Creating secure and sustainable digital environments depends heavily on integrating such innovations. Our model’s ability to accurately detect network anomalies demonstrates the potential of CNNs to revolutionize cybersecurity practices. this study advocates for the continued application of deep learning methods to address the growing challenges in cybersecurity, contributing to the achievement of key sustainable development goals while ensuring the stability and security of digital systems.

关键词： Deep learning Training Technological innovation Accuracy Telecommunication traffic Convolutional neural networks computer security Sustainable development Anomaly detection Resilience

来源：评论

学校读者我要写书评

暂无评论

Deep learning Forecast of Cognitive Workload Using fNIRS Data

Deep Learning Forecast of Cognitive Workload Using fNIRS Dat...

引用

IEEE international conference on Human-machine Systems

作者： Nicolas Grimaldi Yunmei Liu Ryan McKendrick Jaime Ruiz David Kaber Industrial and Systems Engineering University of Florida Gainesville FL USA Industrial Engineering University of Louisville Louisville KY USA Mission Systems Northrop Grumman Falls Church VA USA Computer & Information Science & Engineering University of Florida Gainesville FL USA

ISBN: (数字)9798350315790

ISBN: (纸本)9798350315806

Introduction: In the domain of helicopter piloting, the pilot’s performance is driven by many cognitive processes, demanding substantial cognitive resources. the pilot must maintain situation awareness and perform rapid decision-making. An objective of integrated helicopter technologies is to predict and effectively manage pilot cognitive workload to ensure safety and efficiency throughout flight. Methods: In this study, we collected data on seven participants, including three experienced pilots, using a UH-60V cockpit simulator to perform 46 distinct trials under various flight conditions. fNIRS neuroimaging was used to collect high-resolution neurophysiological data for exploring and forecasting cognitive workload using a collection of deep learning models. Model implementation: three deep learning architectures are detailed in this work: a stacked LSTM model, a CNN-LSTM hybrid, and a transformer model. Results: An evaluation of three Seq2Seq models, each with two distinct forecasting lengths (10s and 30s), revealed LSTM-based architectures as superior performers for 10s forecasting tasks. Discussion: the LSTM-based models’ superior performance suggested potential limitations with the transformer’s self-attention mechanisms for our specific application. Surprisingly, the CNN-LSTM architecture did not surpass the stacked LSTM model’s performance during forecasting tasks. Conclusion: Future research directions include exploring diverse time-series Seq2Seq methods and forecasting cognitive workload as ordinal measures, offering insights into shifting cognitive demands.

关键词： Deep learning Analytical models Predictive models Transformers Data models Real-time systems Safety

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418页 << < 406 407 408 409 410 411 412 413 414 415 > >>

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：