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

1,381 篇 会议
25 册 图书
20 篇 期刊文献

馆藏范围

1,426 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,206 篇 工学
- 987 篇 计算机科学与技术...
- 809 篇 软件工程
- 268 篇 信息与通信工程
- 146 篇 生物工程
- 125 篇 生物医学工程（可授...
- 119 篇 控制科学与工程
- 82 篇 电气工程
- 71 篇 光学工程
- 70 篇 机械工程
- 67 篇 电子科学与技术（可...
- 49 篇 安全科学与工程
- 48 篇 化学工程与技术
- 44 篇 仪器科学与技术
- 40 篇 土木工程
536 篇 理学
- 286 篇 数学
- 166 篇 生物学
- 122 篇 物理学
- 108 篇 统计学（可授理学、...
- 65 篇 系统科学
- 44 篇 化学
343 篇 管理学
- 181 篇 管理科学与工程(可...
- 181 篇 图书情报与档案管...
- 117 篇 工商管理
113 篇 医学
- 110 篇 临床医学
- 103 篇 基础医学(可授医学...
- 64 篇 药学(可授医学、理...
- 45 篇 公共卫生与预防医...
71 篇 法学
- 61 篇 社会学
60 篇 教育学
- 60 篇 教育学
52 篇 农学
- 49 篇 作物学
33 篇 经济学
4 篇 军事学
2 篇 文学
1 篇 艺术学

主题

22 篇 students
20 篇 internet of thin...
19 篇 machine learning
18 篇 computer vision
16 篇 support vector m...
16 篇 convolutional ne...
15 篇 semantics
14 篇 deep learning
12 篇 feature extracti...
12 篇 accuracy
12 篇 technological in...
11 篇 human computer i...
11 篇 wireless sensor ...
11 篇 visualization
11 篇 decision trees
11 篇 virtual reality
11 篇 multi agent syst...
10 篇 e-learning
10 篇 adversarial mach...
10 篇 social networkin...

机构

6 篇 department of co...
5 篇 beijing research...
5 篇 school of comput...
5 篇 department of co...
5 篇 department of co...
5 篇 department of co...
5 篇 school of comput...
4 篇 university of sc...
4 篇 key laboratory o...
4 篇 gits udaipur
4 篇 lovely professio...
4 篇 insight sfi rese...
4 篇 department of co...
4 篇 mlr institute of...
4 篇 school of comput...
4 篇 department of co...
4 篇 college of infor...
4 篇 institute of com...
3 篇 school of softwa...
3 篇 beijing laborato...

作者

7 篇 sun fuchun
7 篇 harris frederick...
6 篇 bein doina
6 篇 vani v.
6 篇 karthik n.
5 篇 tyagi vipin
5 篇 yang yujian
4 篇 rajalakshmi s.
4 篇 jose joemon m.
4 篇 sharma ajay kuma...
4 篇 ootsu kanemitsu
4 篇 rathore narendra...
4 篇 patel mayank
4 篇 yokota takashi
4 篇 baba takanobu
4 篇 angel deborah s.
4 篇 pan jeng-shyang
4 篇 chakravarthi bha...
4 篇 shi zhongzhi
3 篇 shen chen

语言

1,379 篇 英文
35 篇 其他
29 篇 中文

检索条件"任意字段=7th IASTED International Conference on Advances in Computer Science and Technology"

共 1426 条记录，以下是71-80 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：

Ensemble Federated Learning for Classifying IoMT Data Streams 7

Ensemble Federated Learning for Classifying IoMT Data Stream...

引用

7th IEEE international conference for Convergence in technology, I2CT 2022

作者： Arya, Monika Hanumat Sastry, G. Bhilai Institute of Technology Dept of Computer Science & Engineering Durg India University of Petroleum and Energy Studies School of Computer Science Dehradun India

ISBN: (纸本)9781665421683

Recent advances in Internet-of-Medical-things have transformed smart healthcare enabled by artificial intelligence (AI). However, to train classical AI-based machine learning (ML) and deep learning (DL) models, patients' data from individual devices, sensors, and wearables must be uploaded to central servers. this is infeasible in realistic healthcare scenarios as it may result in significant security and privacy issues because of the sensitive nature of healthcare data. Federated Learning (FL) is an emerging distributed collaborative AI paradigm that is particularly attractive for smart healthcare. FL coordinates multiple clients (e.g., hospitals, wearable devices) to train the model without sharing raw data. this paper proposed an ensemble federated learning approach for training a deep learning model for classifying decentralized data streams in IoMT environments. the individual federated models are trained locally, and the ensemble learning is carried out on a server. the results demonstrate that the ensemble federated model outperforms the base federated models. © 2022 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Solar Flare Prediction Using Hybrid CNN-Model 7

Solar Flare Prediction Using Hybrid CNN-Model

引用

7th international conference on Electronics, Materials Engineering and Nano-technology, IEMENTech 2023

作者： Kaur, Ramandeep Yadav, Priya Hariharan, U. Chandigarh University Apex Institute of Technology Department of Computer Science and Engineering Punjab Mohali India

ISBN: (纸本)9798350305517

this paper introduces a hybrid convolutional neural network (CNN) approach to solve the issues given by unpredictable solar flares in space weather forecasting. the methodology, which uses the Solar Dynamics Observatory (SDO) benchmark dataset, combines the robust feature extraction capabilities of VGGNet-16 with the computational efficiency of LeNet. the SDO dataset's input data is carefully preprocessed and shrunk to fit the input size of VGGNet-16, which processes the data to extract complex feature maps capturing minor solar activity patterns. these maps are then transformed to 32x32 to meet the input requirements of LeNet, enabling for accurate classification of solar flares into their appropriate classifications. the experimental results show that the hybrid CNN system outperforms standard approaches in terms of prediction accuracy. the combination of VGGNet-16 feature extraction with LeNet classification improves accuracy while also ensuring computational economy, which is critical for real-time applications. this study represents a big step forward in space weather forecasting, demonstrating the connection between deep learning and heliophysics. the suggested model advances our understanding of solar phenomena by exposing complex patterns underlying solar flares and bridging the gap between observational data and computer models. the discovery holds potential for real-time space weather monitoring, which is critical for satellite operations and terrestrial communication systems. the methodology's efficacy highlights its potential for enhancing astrophysical data processing and space weather forecasting skills, emphasizing the synergy between the technological advancement and scientific research in the field of astrophysics. © 2023 IEEE.

关键词： Computational efficiency

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Analysis of Intrusion Detection Datasets: Evaluation, Challenges, and Insights 7

A Comprehensive Analysis of Intrusion Detection Datasets: Ev...

引用

7th international conference on Image Information Processing, ICIIP 2023

作者： Rani, Seema Kumar, Sanjeev Guru Jambheshwar University of Science And Technology Department of Computer Science And Engineering Hisar India

ISBN: (纸本)9798350371406

Intrusion detection is an important part of cybersecurity, to protect against unauthorized access and malicious activities within computer networks. this paper offers all-inclusive analysis of intrusion detection datasets, that aims to focusing on evaluation, challenges, and the valuable insights they offer to the ground of cybersecurity. Reviewing notable intrusion detection datasets, the paper evaluates each dataset's dimensions, variation, and data distribution. Additionally, issues with intrusion detection dataset adequacy are examined at, including data imbalance, a lack of diversity, and a lack of real-world representation. We learn important things about the positive aspects and negative aspects of employing the datasets that already exist for to this investigation. these observations help us comprehend how dataset quality impacts intrusion detection model performance. this paper accomplishes by offering recommendations and potential directions for the dataset generation, improvement, and sharing of intrusion detection datasets to address these challenges the insights presented in this study aim to direct researchers and practitioners towards better dataset exercise and improved intrusion detection capabilities as the cybersecurity landscape advances. © 2023 IEEE.

关键词： Intrusion detection

来源：评论

学校读者我要写书评

暂无评论

Analysis of Data Transforming technology for Malware Detection 7

Analysis of Data Transforming Technology for Malware Detecti...

引用

7th IEEE/ACIS international conference on Big Data, Cloud Computing, and Data science, BCD 2022

作者： Han, Sung-Hwa Tonmyong University Dept. of Information Security Busan Korea Republic of

ISBN: (数字)9781665465823

ISBN: (纸本)9781665465823

As AI technology advances and its use increases, efforts to incorporate machine learning for malware detection are increasing. However, for malware learning, a standardized data set is required. Because malware is unstructured data, it cannot be directly learned. In order to solve this problem, many studies have attempted to convert unstructured data into structured data. In this study, the features and limitations of each were analyzed by investigating and analyzing the method of converting unstructured data proposed in each study into structured data. As a result, most of the data conversion techniques suggest conversion mechanisms, but the scope of each technique has not been determined. the resulting data set is not suitable for use as training data because it has infinite properties. © 2022 IEEE.

关键词： Malware

来源：评论

学校读者我要写书评

暂无评论

Kinect Sensor-Based Indoor 3D Reconstruction - A Pilot Study 7

Kinect Sensor-Based Indoor 3D Reconstruction - A Pilot Study

引用

7th IEEE international conference on Computational Systems and Information technology for Sustainable Solutions, CSITSS 2023

作者： Amruth Mandappa, T.S. Pavan Kumar, B.N. Chakravarthi, Bharatesh Manjunath, V. Girish, N. Prabhu Prasad, M. Iiit Dharwad Dept. of Cse India Iiit Sri City Dept. of Cse India Scai Arizona State University Active Perception Group United States Iiit Dharwad Dept. of Data Science and Intelligent Systems India

ISBN: (纸本)9798350343144

this study investigates the application of a low-cost Kinect sensor for 3D reconstruction inside. the project uses structured light technologies and the Kinect depth sensor to collect and rebuild interior surroundings in three dimensions. the primary goal is to provide realistic 3D representations of interior locations for a variety of purposes. Using the Kinect sensor and specialized software, interior scenes are scanned and then recreated. the outcomes indicate how well the Kinect-based method works for producing accurate indoor 3D reconstructions, and also suggest possible uses for it in a number of industries, including robotics, virtual reality, and architectural visualization. this work advances the use of Kinect sensors for indoor 3D reconstruction, providing new opportunities for improved spatial comprehension and virtual environment engagement. © 2023 IEEE.

关键词： three dimensional computer graphics

来源：评论

学校读者我要写书评

暂无评论

COOL: Classification of Online Offensive Language Using Machine Learning and Deep Learning 7th

COOL: Classification of Online Offensive Language Using Mach...

引用

7th IFIP TC 12 international conference on Computational Intelligence in Data science, ICCIDS 2024

作者： Bhamidi, Manjari Nandyala, Manvitha Dayalan, Ragapriya Karthik, N. Vani, V. Department of Computer Science and Engineering National Institute of Technology Puducherry Karaikal Puducherry609609 India Department of Civil Engineering National Institute of Technology Puducherry Karaikal Puducherry609609 India

ISBN: (纸本)9783031699818

In the dynamic realm of online communication, the surge in offensive language and hate speech has emerged as a critical concern. the proliferation of digital platforms has led to a distressing uptick in such behaviors, challenging the establishment of a secure and inclusive online environment. Identifying and categorizing such conduct is imperative from both an ethical standpoint and for the prevention of further harm. the training and validation dataset encompass a diverse array of online platforms, ensuring inclusivity across various communication styles and linguistic nuances. To capture the nuanced characteristics of abusive language, a range of feature extraction techniques were included, consisting of traditional NLP methods and state-of-the-art deep learning architectures. In tandem with these approaches, comprehensive experiments employing a variety of classifiers, such as logistic regression, SVM, stochastic gradient descent, decision trees, and ensemble models were conducted. In summary, this research contributes significantly to the ongoing battle against online toxicity and the promotion of more constructive online conversations. the RNN algorithm’s 99.47% accuracy rate in detecting hate speech has significant societal and platform-level ramifications. It represents a strong barrier against hate speech spreading online, creating a safer atmosphere. © IFIP international Federation for Information Processing 2024.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Advancements in Brain Tumor Detection using Machine Learning Applications from MRI Image Analysis 7

Advancements in Brain Tumor Detection using Machine Learning...

引用

7th international conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2023

作者： Sneha, Yerram Roopa, Y Mohana Sawant, Padmini Rao, M Varaprasad Padmaja, D Lakshmi Lalitha, R.V.S. Kl University Department of Cse Hyderabad India Institute of Aeronautical Engineering Department of Cse Telangana Hyderabad India Bharati Vidyapeeth College of Engineering Department of Mechanical Engineering Navi Mumbai India Cvr College of Engineering Department of Computer Science and Engineering Hyderabad India Anurag University Department of Information Technology Telangana Hyderabad500088 India Aditya College of Engineering & Technology Department of Computer Science and Engineering India

ISBN: (纸本)9798350341485

the present research uses a dataset of 2034 images to conduct a detailed evaluation of machine learning models for the purpose of identifying brain tumours in MRI scans. Convolutional Neural Networks (CNN), Support Vector Machines (SVM), Random Forest (RF), and Logistic Regression (LR) were four alternative models that were thoroughly examined based on their performance indicators. the Convolutional Neural Network was shown to be the most effective model, with a high accuracy of 97.5%, great precision, recall, and F1 scores. this demonstrates how deep learning, namely CNNs, can be used to automate and improve brain tumour identification in medical imaging. the study also underlines the SVM and RF models' durability and adaptability, which demonstrated exceptional performance metrics and were thus acceptable for use in real-world healthcare applications. Despite having substantially lower scores, the Logistic Regression model also significantly aids in diagnosis. Finally, this study demonstrates the importance of machine learning in the medical business and the potential for early brain tumour detection, which would improve patient care and treatment outcomes. It emphasises how the field of medical image analysis is always evolving and improving, meaning advances in the detection and management of major medical disorders. © 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

A Comprehensive Overview on IoT-Based Smart Stroke Rehabilitation Using the advances of Wearable technology 23

A Comprehensive Overview on IoT-Based Smart Stroke Rehabilit...

引用

23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Razfar, Najmeh Kashef, Rasha Mohammadi, Farah Ryerson University Electrical and Computer Engineering Toronto Canada

ISBN: (纸本)9781665494571

the Internet of things (IoT) is growing fast, and with the advancement of wearable devices and sensors, a wide range of research opportunities is now available. Several machine learning and deep learning techniques were deployed to provide smart stroke rehabilitation in remote stroke treatment and assessments. Reviewing and understanding existing studies in IoT-based stroke rehabilitation and finding the gap in this field can improve rehabilitation strategy. this paper summarizes the development of smart stroke rehabilitation knowledge for remote rehabilitation and assessments of stroke survivors. We have summarised the datasets and the state-of-the-art machine learning and deep learning methods in the IoT-based smart stroke rehabilitation using wearable devices. Supervised learning is the most common technique reported for stroke rehabilitation, and the optimum model is also reported in this paper. this survey provides a novel roadmap for future research in IoT-based stroke rehabilitation and treatment. © 2021 IEEE.

关键词： Deep learning Smart cities Wearable computers Supervised learning Stroke (medical condition) Sensor systems Internet of things

来源：评论

学校读者我要写书评

暂无评论

MUCS@LT-EDI2023: Homophobic/Transphobic Content Detection in Social Media Text using mBERT 3

MUCS@LT-EDI2023: Homophobic/Transphobic Content Detection in...

引用

3rd Workshop on Language technology for Equality, Diversity and Inclusion, LTEDI 2023

作者： Hegde, Asha Kavya, G. Coelho, Sharal Shashirekha, Hosahalli Lakshmaiah Department of Computer Science Mangalore University Mangalore India

ISBN: (纸本)9789544520847

Homophobic/Transphobic (H/T) content includes hate speech, discrimination text, and abusive comments against Lesbian, Gay, Bisexual, Transgender, and Queer (LGBTQ) individuals. With the increase in user generated text in social media, there has been an increase in H/T content also. Further, most of the text data on social media is code-mixed and this poses challenges for efficient analysis and detection of H/T content on social media. the complex nature of code-mixed text necessitates the development of advanced tools and techniques to effectively tackle this issue on social media platforms. Hence, in this paper, we - team MUCS, describe the transformer based models submitted to"Homophobia/Transphobia Detection in social media comments" shared task in Language technology for Equality, Diversity and Inclusion (LT-EDI) at Recent advances in Natural Language Processing (RANLP)-2023. the proposed methodology makes use of oversampling technique to handle data imbalance in the given Train set and this oversampled data is used to fine-tune the Transfer Learning (TL) based Multilingual Bidirectional Encoder Representations from Transformers (mBERT) models. these models obtained weighted F1 scores of 0.91, 0.91, 0.95, 0.94, and 0.81 securing 11th, 5th, 3rd, 3rd, and 7th ranks for English, Tamil, Malayalam, Spanish, and Hindi languages respectively in Task A and weighted F1 scores of 0.14, 0.82, and 0.85 securing 8th, 2nd, and 2nd ranks for English, Tamil, and Malayalam languages respectively in Task B. © 2023 LTEDI 2023 - 3rd Workshop on Language technology for Equality, Diversity and Inclusion, associated with the 14th international conference on Recent advances in Natural Language Processing, RANLP 2023 - Proceedings. All rights reserved.

关键词： Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

Application of Phonocardiogram and Electrocardiogram Signal Features in Cardiovascular Abnormality Recognition 7th

Application of Phonocardiogram and Electrocardiogram Signa...

引用

7th international conference on computer, Communication and Signal Processing, ICCCSP 2023

作者： Ramani, R. Geetha Ganesh, Abhinand Balasubramanian, Roshni Ramkumar, Aruna Srikamakshi Department of Information Science and Technology CEG Anna University Chennai600 025 India

ISBN: (纸本)9783031398100

Globally, cardiovascular disorders are the leading cause of death. the current situation calls for a precise method to determine whether a person’s heartbeat and heart signals are irregular. Electrocardiograms (ECG) and phonocardiograms (PCGfor) are techniques to identifying cardiovascular abnormalities in modern medicine. As the first step in the diagnosis, sound waves from heartbeats could be classified as normal or abnormal. In order to predict the presence of cardiovascular abnormalities, our study compares the use of ECG, PCG, and a hybrid feature approach. the PhysioNet/CinC 2016 and PhysioNet/CinC 2017 datasets were used. With the AdaBoost ensemble classifier using Random Forest as the base model, it has been found that the PCGwith-ECG hybrid feature strategy outperforms the former methodologies in terms of sensitivity with a score of 95.16 © IFIP international Federation for Information Processing 2023.

关键词： Electrocardiograms

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143页 << < 4 5 6 7 8 9 10 11 12 13 > >>

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：