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

16,099 篇 会议
2,501 篇 期刊文献
147 册 图书

馆藏范围

18,747 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

11,225 篇 工学
- 7,578 篇 计算机科学与技术...
- 6,334 篇 软件工程
- 3,208 篇 信息与通信工程
- 1,875 篇 控制科学与工程
- 1,712 篇 电子科学与技术（可...
- 1,701 篇 电气工程
- 1,166 篇 生物工程
- 1,029 篇 生物医学工程（可授...
- 874 篇 光学工程
- 754 篇 机械工程
- 698 篇 动力工程及工程热...
- 688 篇 仪器科学与技术
- 574 篇 化学工程与技术
- 473 篇 安全科学与工程
- 418 篇 交通运输工程
- 373 篇 材料科学与工程（可...
5,787 篇 理学
- 3,018 篇 数学
- 1,776 篇 物理学
- 1,276 篇 生物学
- 984 篇 统计学（可授理学、...
- 668 篇 系统科学
- 578 篇 化学
2,736 篇 管理学
- 1,684 篇 管理科学与工程(可...
- 1,205 篇 图书情报与档案管...
- 883 篇 工商管理
864 篇 医学
- 759 篇 临床医学
- 707 篇 基础医学(可授医学...
- 451 篇 药学(可授医学、理...
- 363 篇 公共卫生与预防医...
498 篇 法学
- 397 篇 社会学
326 篇 经济学
236 篇 农学
206 篇 教育学
78 篇 文学
44 篇 军事学
15 篇 艺术学
1 篇 历史学

主题

527 篇 accuracy
398 篇 feature extracti...
393 篇 deep learning
386 篇 computational mo...
288 篇 support vector m...
278 篇 training
275 篇 real-time system...
260 篇 internet of thin...
224 篇 machine learning
221 篇 optimization
213 篇 predictive model...
197 篇 computer science
195 篇 computer archite...
179 篇 neural networks
176 篇 wireless communi...
175 篇 reliability
171 篇 data mining
163 篇 convolutional ne...
161 篇 routing
160 篇 wireless sensor ...

机构

84 篇 institut univers...
82 篇 north-west unive...
82 篇 national centre ...
82 篇 tno technical sc...
79 篇 infn sezione di ...
79 篇 nikhef national ...
78 篇 university würzb...
78 篇 university of jo...
76 篇 infn sezione di ...
76 篇 université de st...
66 篇 università di ca...
65 篇 ncsr demokritos ...
64 篇 university moham...
54 篇 university moham...
53 篇 leiden universit...
51 篇 dept. of compute...
50 篇 school of automa...
43 篇 in2p3 lpc campus...
42 篇 infn lnf via enr...
41 篇 university of gr...

作者

85 篇 ferrara g.
85 篇 ardid m.
84 篇 calvo d.
84 篇 gal t.
84 篇 bozza c.
82 篇 kalekin o.
82 篇 díaz a.f.
82 篇 boumaaza j.
82 篇 coleiro a.
81 篇 chen a.
81 篇 gozzini s.r.
81 篇 dallier r.
78 篇 anguita m.
78 篇 enzenhöfer a.
76 篇 boettcher m.
75 篇 celli s.
73 篇 aly z.
72 篇 dornic d.
70 篇 huang f.
70 篇 carretero v.

语言

17,998 篇 英文
485 篇 其他
190 篇 中文
51 篇 日文
21 篇 朝鲜文
1 篇 阿拉伯文
1 篇 德文
1 篇 法文
1 篇 斯洛文尼亚文
1 篇 土耳其文

检索条件"机构=Dept. of Computer Engineering and Informatics and Computer Technology"

共 18747 条记录，以下是141-150 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：

TrustCaller- Voice-based Fraud Prevention System 4

TrustCaller- Voice-based Fraud Prevention System

引用

4th International Conference on Intelligent Technologies, CONIT 2024

作者： Sonwane, Rushikesh Patil, Mansi Chauhan, Purva Jain, Anushka Nandwalkar, Bhushan Awate, Ashish Shahade, Makarand SVKM's Institute of Technology Dept. of Computer Engineering Dhule India

ISBN: (纸本)9798350349900

An innovative project called 'TrustCaller' aims to improve call security. With the goal of establishing caller verification and building trust in incoming calls, the project makes use of state-of-the-art technologies for voice feature extraction, processing, and pattern matching. Utilizing React Native only for the Android application, 'TrustCaller' assumes a key function in boosting the security of phone communications when combined with Machine Learning (ML) and Speech Synthesis. This program is a vital step in protecting people from possible dangers and promoting safer phone communication. Moreover, it provides scalable security settings to guarantee users' privacy and control over communication. © 2024 IEEE.

关键词： Secure communication

来源：评论

学校读者我要写书评

暂无评论

TotCareBot: A Comprehensive Approach Towards Enhancing Early Childhood Education through Robotics 5

TotCareBot: A Comprehensive Approach Towards Enhancing Early...

引用

5th International Conference on Circuits, Control, Communication and Computing, I4C 2024

作者： Chougala, Manjula R Sushma, B. Bhayyar, Akshata S Bhandarkar, Abhay Pavithra, P.N. Ramaiah Institute of Technology Dept. of Computer Science and Engineering Bangalore India Ramaiah Institute of Technology Department of Computer Science Engineering Bengaluru India

ISBN: (纸本)9798331528539

Robots have emerged as versatile tools with significant potential to enhance teaching and learning environments, including classrooms, laboratories, play homes, crèches, and even at home. Their engaging nature can captivate young children, boosting motivation and interest. This paper proposes a methodology for an Educational Robot (ER) designed for play homes. The ER is capable of moving around the classroom, monitoring children, analyzing their emotions, responding appropriately, and alerting the teacher when necessary. The proposed system aims to leverage the positive impact of expressive behaviors in robots, such as storytelling and pampering. Our findings indicate that expressive robot narration is as effective as that of a human displaying similar behaviors and even surpasses a static, inexpressive human narrator. Furthermore, the robot excels in conveying educational content, although its limited emotional expression slightly reduces its effectiveness in narrating emotionally rich stories. This research underscores the potential of ERs to create dynamic and interactive learning experiences for young children, fostering both their cognitive and emotional development. © 2024 IEEE.

关键词： Educational robots

来源：评论

学校读者我要写书评

暂无评论

Homogenous Ensemble Learning for Air Quality Index Prediction 15

Homogenous Ensemble Learning for Air Quality Index Predictio...

引用

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Medhi, Shrabani Boruah, Rituraj Baruah, Sagar Pratim Das, Hiranya Kumar Girijananda Chowdhury University Dept. of Computer Science and Engineering Guwahati India Girijananda Chowdhury Institute of Management and Technology Dept. of Computer Science and Engineering Guwahati India

ISBN: (纸本)9798331300579

Air pollution is a global issue of concern. Accurate prediction of the air quality index (AQI) plays a crucial role in understanding pollution patterns and implementing effective mitigation strategies. This research paper presents a comprehensive study on the application of ensemble learning techniques for AQI prediction, aiming to enhance prediction accuracy and provide insights into the driving factors behind pollution levels. The primary objective is to conduct a comparative analysis of homogenous ensemble method, namely, bagging in conjunction with individual base models, such as multiple linear regression, support vector regression, decision trees, and artificial neural networks. In total we have created 4 non-ensembled models and 4 ensembled models. Additionally, the research investigates the importance of different features in AQI prediction models, aiming to identify the key factors influencing air pollution. Hyperparameter tuning is done to optimize the models. © Grenze Scientific Society, 2024.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

PhishGuard: A Convolutional Neural Network-Based Model for Detecting Phishing URLs with Explainability Analysis 3

PhishGuard: A Convolutional Neural Network-Based Model for D...

引用

3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Islam, Md Robiul Islam, Md Mahamodul Afrin, Mst. Suraiya Antara, Anika Tabassum, Nujhat Amin, Al Uttara University Dept. of Computer Science and Engineering Dhaka Bangladesh University of Oslo Dept. of Informatics Oslo Norway Dept. of Building Engineering and Construction Management Khulna Bangladesh BRAC University Dept. of Electrical and Electronics Engineering Dhaka Bangladesh North South University Dept. of Electrical and Computer Engineering Dhaka Bangladesh Dept. of Computer Science American International Dhaka Bangladesh

ISBN: (纸本)9798350372120

Cybersecurity is one of the global issues because of the extensive dependence on cyber systems of individuals, industries, and organizations. Among the cyber attacks, phishing is increasing tremendously and affecting the global economy. Therefore, this phenomenon highlights the vital need for enhancing user awareness and robust support at both individual and organizational levels. Phishing URL identification is the best way to address the problem. Various machine learning and deep learning methods have been proposed to automate the detection of phishing URLs. However, these approaches often need more convincing accuracy and rely on datasets consisting of limited samples. Furthermore, these black-box intelligent models' decision to detect Suspicious URLs needs proper explanation to understand the features affecting the output. To address the issues, we propose a 1 D Convolutional Neural Network (CNN) and trained the model with extensive features and a substantial amount of data. The proposed model outperforms existing works by attaining an accuracy of 99.85 %. Additionally, our explainability analysis highlights certain features that significantly contribute to identifying the phishing URL. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Analytical Approach Towards Radiological Image-based Fracture Assessment Using Artificial Intelligence 1

Analytical Approach Towards Radiological Image-based Fractur...

引用

1st International Conference on Computing, Sciences and Communications, ICCSC 2024

作者： Sylvia, Takhellambam Dubey, Sanjay Kumar Thongam, Khelchandra Amity University Computer Science & Engineering Dept. Uttar Pradesh Noida India National Institute of Technology Manipur Computer Science & Engineering Dept. Imphal India

ISBN: (纸本)9798350353648

The utilization of Artificial Intelligence (AI) techniques has been prevalent in various applications and the gradual increase in implementation towards healthcare sectors has scaled up. computer aided diagnosis has emerged as a major research area directed toward efficient use of resources. Fracture of bone has been a popular health problem associated with risk for mortality. Fractures are frequent in the long bones or the weight-bearing bones. AI techniques to accurately detect and classify fractures are still a challenging task beyond the conventional methods. Our objective is to assess the effectiveness of multiple algorithms in identifying and categorizing ankle fractures using radiological images. This review paper focuses on several available approaches of Deep-Learning (DL) and Machine-Learning (ML) regarding Ankle Fracture Classification and Identification based on Radiological Images for Medical Applications. The goal is to assist physicians and orthopaedics with simple and realistic decision support systems. In addition to a comprehensive analysis of the research, this study looked at several real-world examples of AI applications in the healthcare industry. Consequently, it is critical to have a fundamental grasp of these ML and DL algorithms to be ready for upcoming advancements in AI. We have reviewed and classified scientific conference and journal articles used for various AI techniques and offer future utility as a comparative analysis for further research in healthcare sectors. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Detection of Cardiovascular Disease from ECG Image Using Optimized Weighted Average Ensemble Machine Learning Technique 26

Detection of Cardiovascular Disease from ECG Image Using Opt...

引用

26th International Conference on computer and Information technology, ICCIT 2023

作者： Hasan, Md. Nahid Hossain, Md. Ali Akash, Ahsan Sadek Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Bangladesh Pabna University of Science & Technology Dept. of Computer Science & Engineering Bangladesh

ISBN: (纸本)9798350359015

cardiovascular diseases (CVD) stand as a prominent global cause of death in worldwide. Timely identification and intervention are paramount in dealing with heart disease, as its failure to detect and treated promptly can lead to life-threatening outcomes. The Electrocardiogram (ECG) Signals are mainly used as diagnostic tools that routinely assess the electrical and muscular function of the heart. Until recently, ECG records were predominantly maintained in paper form;thus, manually examining and re-examining the ECG paper records are often proved time-consuming and laborious tasks. Therefore, this research work utilizes, the power of machine learning and deep learning in predicting four different cardiac abnormalities named Abnormal Heartbeats (AHB), History of Myocardial Infarction (HMI), Myocardial Infarction (MI), and Normal Heartbeats (NHB) from paper-based ECG images. Different image pre-processing methods have been employed to improve the quality of individual ECG images and a novel lightweight deep neural model is proposed for extracting prominent features from each ECG images. Finally, we used an optimized weighted average ensemble technique for the final prediction. The grid search technique is used to find the optimal parameters and weights of each machine-learning model. Our proposed model shows state-of-the-art results in accuracy, precision, recall, and f1-score of 99.29%, outperforming the existing work. The model has attained an Area Under Curve (AUC) score of 99.96%. © 2023 IEEE.

关键词： Cardiovascular disease convolution neural network (CNN) deep learning ECG image feature extraction image classification machine learning weighted average ensemble

来源：评论

学校读者我要写书评

暂无评论

Linear Irrational Unit (LIU): An Activation Function For Convolutional Neural Network 5

Linear Irrational Unit (LIU): An Activation Function For Con...

引用

5th IEEE International Conference on Communication, Computing and Industry 6.0, C2I6 2024

作者： Nanda, Pranamita Duraipandian, N. Behera, Sagarika R.M.K College of Engineering and Technology Dept. of Computer Sc. and Engineering Tamilnadu 601206 India Rajalakshmi Engineering College Dept. of Computer Sc. and Engineering Tamilnadu Chennai602105 India Cmr Institute of Technology Dept. of Computer Sc. and Engineering Bengaluru560037 India

ISBN: (纸本)9798350379884

In a convolutional neural network (CNN), the output is produced by passing the input through an activation function (AF). The traditional AFs like sigmoid and tanh suffer from disappearing gradient problems. The disappearing gradient issue was solved by the ReLU AF, but the negative region issue still exists. This study introduces a non-monotonic, nonlinear AF dubbed the Linear Irrational Unit (LIU). The function is continuously differentiable in both the positive and negative regions, which overcomes the disappearing gradient problem. As the proposed function has a non-zero value in the negative region, it does not suffer from the negative region problem. The effectiveness of the proposed LIU activation function was assessed using MNIST, CIFAR-10 and Chest X-ray datasets. With our proposed CNN model, the LIU activation function can reach an accuracy of 85.26% on the Chest X-ray dataset, 99.52% on the MNIST dataset, and 83.15% on the CIFAR dataset, which is better than the performance of other modern activation functions. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Automated Bengali Sign Language Character Classification with Deep Learning Techniques 15

Automated Bengali Sign Language Character Classification wit...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Akter, Tahmina Mahmud, Tanjim Barua, Tikle Naher, Sultana Rokeya Hossain, Mohammad Shahadat Andersson, Karl Port City International University Dept. of Computer Science and Engineering Chittagong Bangladesh Rangamati Science and Technology University Dept. of Computer Science and Engineering Rangamati4500 Bangladesh University of Information Technology and Sciences Dept. of Computer Science and Engineering Dhaka Bangladesh University of Chittagong Dept. of Computer Science and Engineering Chittagong4331 Bangladesh Luleå University of Technology Cybersecurity Laboratory Luleå97187 Sweden

ISBN: (纸本)9798350370249

Recognition of Bengali sign language characters is crucial for facilitating communication for the deaf and hard-of-hearing population in Bengali-speaking regions, which encompass approximately 430 million people worldwide. Despite the significant number of individuals requiring this support, research on Bengali sign language character recognition remains underdeveloped. This article presents a novel approach to categorize Bengali sign language characters using the Ishara-Lipi dataset, based on convolutional neural networks (CNNs) and pretrained models. We evaluated our approach using metrics such as accuracy, precision, recall, F1-score, and confusion matrices. Our findings indicate that the CNN model achieved the highest performance with an accuracy of 98%, followed by VGG19 with 94% and ResNet variants achieving around 88%. The proposed model demonstrates robust and efficient classification capabilities, significantly bridging the gap in existing literature. This study holds substantial promise for enhancing assistive technology, thereby improving social inclusion and quality of life for Bengalispeaking deaf and hard-of-hearing individuals. © 2024 IEEE.

关键词： Bengali sign language CNNs Deaf and hard-of-hearing community Image classification

来源：评论

学校读者我要写书评

暂无评论

Implementing a Robust and Scalable Detect-and-Avoid Algorithm for UAV Navigation in ROS 15

Implementing a Robust and Scalable Detect-and-Avoid Algorith...

引用

15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Meimetis, Dimitrios Daramouskas, Ioannis Lappas, Vaios Perikos, Isidoros Kapoulas, Vaggelis Paraskevas, Michael Nkua Department of Aerospace Science & Technology Athens Greece Computer Technology Institute and Press 'Diophantus' Patras Greece UoP Applied Mechanics Lab Patras Greece UoP Computer Engineering and Informatics Department Patras Greece Computer Technology Institute and Press 'Diophantus' University of Peloponnese Electrical and Computer Engineering Dept. Patras Greece

ISBN: (纸本)9798350368833

Unmanned aerial vehicles (UAVs) have garnered significant attention from the research community during the last decade, due to their diverse capabilities and potential applications. One of the most critical functions that drones must execute efficiently is navigation in real-world environments. This paper presents a decentralized approach for enabling unmanned aerial vehicles (UAVs) to navigate safely in unknown environments and avoid obstacles. Leveraging the Optimal Reciprocal Collision Avoidance (ORCA) algorithm, implemented in the Robot Operating System (ROS), our method facilitates conflict detection and resolution in 2D environments. Through simulations using ROS, Gazebo, and Iris drones, we validate the effectiveness of our approach in scenarios with initial trajectory conflicts. Our work addresses the pressing need for UAVs to autonomously plan and execute safe flights, laying the groundwork for enhanced UAV capabilities in various real-world applications. The simulation results demonstrate the efficiency and robustness of our approach. © 2024 IEEE.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Multispectral Images and IoT Based Tea Plantation Monitoring: A Proposed System Architecture 5

Multispectral Images and IoT Based Tea Plantation Monitoring...

引用

5th International Conference on Advanced Research in Computing, ICARC 2025

作者： Kariyawasam, K.P.W.D.V. Kahandagamage, P.N. Fernando, M.R.R. Fernandopulle, J.M. Jayasinghearachchi, Vishan Dissanayaka, Kapila Dept. of Software Engineering Sri Lanka Dept. of Information Technology Sri Lanka Dept. of Computer Science Sri Lanka

ISBN: (纸本)9798331530983

In recent years, the Sri Lankan tea industry has fallen behind its competitors in the global tea market. This decline is caused by the challenges in productivity and resource management due to the limitations of traditional crop monitoring methods. This study presents a prototype system architecture that integrates multispectral imagery and IoT technologies to enhance plantation monitoring. The proposed system uses drones to capture high-resolution multispectral images and IoT devices to collect real-time environmental data, providing a comprehensive approach to assessing plant yield and detecting stress. Built on a hexagonal architecture, the system emphasizes modularity, reliability, and scalability by ensuring a clear separation of core functionalities from external components. This design facilitates easy adaptation to various crop types and agricultural contexts, enabling flexibility in deployment and use. This flexible framework can serve as a blueprint for improving decision-making and management practices across diverse plantation environments. © 2025 IEEE.

关键词： Risk perception

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 << < 11 12 13 14 15 16 17 18 19 20 > >>

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：