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

176,544 篇 会议
76,158 篇 期刊文献
1,852 册 图书
3 篇 学位论文

馆藏范围

254,557 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

150,608 篇 工学
- 101,370 篇 计算机科学与技术...
- 82,965 篇 软件工程
- 38,260 篇 信息与通信工程
- 24,205 篇 控制科学与工程
- 20,376 篇 电气工程
- 19,634 篇 电子科学与技术（可...
- 17,801 篇 生物工程
- 13,103 篇 生物医学工程（可授...
- 12,240 篇 光学工程
- 11,373 篇 机械工程
- 8,857 篇 化学工程与技术
- 8,452 篇 仪器科学与技术
- 8,331 篇 动力工程及工程热...
- 6,580 篇 材料科学与工程（可...
- 6,181 篇 网络空间安全
- 5,937 篇 安全科学与工程
- 5,683 篇 交通运输工程
83,795 篇 理学
- 41,660 篇 数学
- 26,791 篇 物理学
- 19,865 篇 生物学
- 13,552 篇 统计学（可授理学、...
- 9,335 篇 系统科学
- 9,264 篇 化学
40,238 篇 管理学
- 24,897 篇 管理科学与工程(可...
- 17,055 篇 图书情报与档案管...
- 10,931 篇 工商管理
12,391 篇 医学
- 10,338 篇 临床医学
- 9,442 篇 基础医学(可授医学...
- 5,979 篇 药学(可授医学、理...
6,956 篇 法学
- 5,608 篇 社会学
4,370 篇 经济学
3,635 篇 农学
2,362 篇 教育学
1,211 篇 文学
582 篇 军事学
394 篇 艺术学
23 篇 哲学
16 篇 历史学

主题

7,345 篇 accuracy
7,127 篇 computer science
6,742 篇 feature extracti...
6,317 篇 deep learning
5,765 篇 computational mo...
5,506 篇 training
5,037 篇 machine learning
3,695 篇 predictive model...
3,694 篇 convolutional ne...
3,688 篇 support vector m...
3,443 篇 optimization
3,349 篇 real-time system...
3,183 篇 internet of thin...
3,154 篇 data mining
2,969 篇 data models
2,862 篇 neural networks
2,694 篇 wireless sensor ...
2,609 篇 artificial intel...
2,512 篇 semantics
2,475 篇 security

机构

2,450 篇 school of comput...
2,154 篇 chitkara univers...
1,511 篇 school of comput...
1,329 篇 school of comput...
1,070 篇 cavendish labora...
1,009 篇 college of compu...
969 篇 department of ph...
965 篇 university of ch...
943 篇 school of comput...
897 篇 department of co...
883 篇 physikalisches i...
877 篇 oliver lodge lab...
817 篇 department of el...
725 篇 college of compu...
650 篇 department of co...
649 篇 department of el...
649 篇 school of comput...
553 篇 infn sezione di ...
531 篇 infn sezione di ...
529 篇 infn laboratori ...

作者

293 篇 niyato dusit
250 篇 barter w.
248 篇 a. gomes
242 篇 s. chen
235 篇 c. alexa
235 篇 j. wang
230 篇 j. m. izen
227 篇 blake t.
221 篇 bellee v.
219 篇 bowcock t.j.v.
218 篇 amato s.
217 篇 betancourt c.
215 篇 borsato m.
214 篇 boettcher t.
211 篇 brundu d.
210 篇 beiter a.
208 篇 c. amelung
208 篇 bencivenni g.
207 篇 g. bella
206 篇 j. strandberg

语言

242,057 篇 英文
9,016 篇 其他
3,480 篇 中文
207 篇 日文
36 篇 朝鲜文
24 篇 德文
23 篇 法文
16 篇 斯洛文尼亚文
6 篇 荷兰文
3 篇 土耳其文
2 篇 俄文
1 篇 阿拉伯文
1 篇 捷克文
1 篇 葡萄牙文

检索条件"机构=Computer Science and Engineering Technology"

共 254557 条记录，以下是4851-4860 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：

EEG-based Emotion Recognition: An In-depth Analysis using DEAP and SEED Datasets 18

EEG-based Emotion Recognition: An In-depth Analysis using DE...

引用

18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Jha, Sonu Kumar Suvvari, Somaraju Kumar, Mukesh National Institute of Technology Patna Department of Computer Science and Engineering Patna India

ISBN: (纸本)9789380544519

Research on emotion recognition has made an increasing amount of emphasis on the understanding of Electroencephalogram (EEG) signals. Using two well-known datasets - the SEED (SEED Dataset for Emotion Analysis using EEG) and the DEAP (Dataset for Emotion Analysis using Physiological Signals), this work explores the complex analysis of EEG signals and their use in emotion recognition. The study highlights important characteristics suggestive of emotional states while delving into the basic ideas behind the acquisition, processing, and interpretation of EEG signals. We explore the viability and efficiency of using EEG signals for emotion recognition tasks by utilizing machine learning and signal processing techniques. We also explore the opportunities and problems associated with EEG-based emotion identification systems, such as feature selection, artefact removal, and signal noise. The goal of this study is to offer researchers and practitioners useful insights into using EEG signals for emotion identification applications through a thorough evaluation and analysis. Showcasing the effectiveness of our methodology in EEG-based emotion recognition. The study demonstrates promising arousal accuracy at 70.88% and notable valence accuracy at 76.00% using SVM Classifier. © 2024 Bharati Vidyapeeth, New Delhi.

关键词： artefact removal DEAP and SEED datasets Electroencephalogram (EEG) feature extraction signal noise

来源：评论

学校读者我要写书评

暂无评论

BeeSense-A Smart Beehive Monitoring System for Sustainable Apiculture 2

BeeSense-A Smart Beehive Monitoring System for Sustainable A...

引用

2nd International Conference on Artificial Intelligence and Machine Learning Applications, AIMLA 2024

作者： Karan, I. Leelipushpam Paulraj, Getzi Jeba Johnraja Jebadurai, Immanuel Jerry Allwin, J. Sharan, D. Sharon Jemimah Peace, C. Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798350349221

BeeSense presents a transformative Smart Beehive Monitoring System designed for Sustainable Apiculture. Utilizing IoT sensors, including load cells for real-time hive weight assessment, temperature/humidity sensors for microclimate insights, ambient light (LDR) sensors, and a microphone for in-depth sound analysis, the system provides a holistic approach to hive monitoring. The strategic positioning of load cells and the integration of a servo motor for gate control enhance precision and security, respectively. Accelerometer sensors further fortify hive security by detecting disturbances. Leveraging Node MCU ESP32, the collected data is seamlessly transmitted to the cloud for analysis. This comprehensive system offers a novel paradigm in beekeeping, optimizing hive management and fostering sustainability, with real-time insights accessible through a mobile or web-based application. © 2024 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Leveraging Machine Learning for Enhanced Software Defect Prediction and Quality Assurance: A Comparative Analysis

Leveraging Machine Learning for Enhanced Software Defect Pre...

引用

2024 International Conference on Computing and Intelligent Reality Technologies, ICCIRT 2024

作者： Mohandas, Parthiban Duraipandian, Amaravathi Chaitanya, Voleti Tharun, Allam Naga Vishnuvardhan, Divi Bala Kumar, Donelli Naga Vinay Computer Science and Engineering Department Sasi Institute of Technology and Engineeering Tadepalligudem India

ISBN: (纸本)9798331510299

The evolution of software engineering practices has heightened the emphasis on quality assurance, particularly in defect prediction and testing methodologies. Traditional approaches often fall short in addressing the complexities of modern software systems, prompting the integration of advanced technologies such as deep learning and machine learning. Recent research highlights the development of robust models for predicting defect density, which effectively tackle issues of data sparsity, alongside the introduction of specialized validation frameworks for AI-driven software that utilize innovative testing methods. Additionally, advancements in automated testing practices, including the use of large language models for test case generation and ensemble machine learning for bug classification, underscore the critical role of efficient maintenance in ensuring software quality. Furthermore, novel frameworks for validating unsupervised learning systems bridge user expectations with system performance evaluations. Collectively, these contributions reveal a trend towards leveraging cutting-edge methodologies to address the multifaceted challenges of software quality, emphasizing the need for adaptive and innovative strategies as software systems continue to evolve. © 2024 IEEE.

关键词： Software quality

来源：评论

学校读者我要写书评

暂无评论

Secure Cloud-Based Diabetes Classification with Machine Learning

Secure Cloud-Based Diabetes Classification with Machine Lear...

引用

2024 International Conference on Artificial Intelligence and Emerging technology, Global AI Summit 2024

作者： Anas, Mohd Hussain, Shahadat Ahmad, Shahnawaz School of Computer Science Engineering and Technology Bennett University Greater Noida India

ISBN: (纸本)9798350379716

With the continuous advancement of medical devices, a substantial amount of data is generated within the healthcare environment daily. Consequently, cloud computing technology is being employed to securely store, process, and manage these vast volumes of data, safeguarding them from potential attacks. This paper focuses on diabetes classification using machine learning (ML) algorithms with a secured cloud computing environment by combining the Elliptic Curve Cryptography (ECC) and the Advanced Encryption Standard (AES) method to ensure authentication and data integrity. Additionally, we performed a comparative analysis of diabetes prediction classification using five diverse ML algorithms. The results show that the random forest (RF) classification method achieves the best results among K-Nearest Neighbors (KNN), Naive Bayes (NB), Diction tree (DT), and support vector machine (SVM) classifiers, with an accuracy of 90.4%, as well as the evaluation of security in the cloud involves analyzing the encryption and decryption times for records of different file sizes, ranging from 20 KB to 50 KB. The results obtained demonstrate that the proposed system surpasses other state-of-the-art systems in terms of performance. Therefore, the proposed model successfully establishes an efficient remote health monitoring system that relies on secure data storage and management on cloud-based platforms. © 2024 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

A Multi-scale Feature Embedding Extension Network for RGB-D Cross-modal Person Re-identification 7

A Multi-scale Feature Embedding Extension Network for RGB-D ...

引用

7th World Conference on Computing and Communication Technologies, WCCCT 2024

作者： Dai, Xuesong Li, Xiaohong Li, Kunyuan Liu, Xueliang Wang, Jing Hefei University of Technology School of Computer Science and Information Engineering Hefei China

ISBN: (纸本)9798350372328

The RGB-D cross-modal person re-identification task is a branch of the cross-modal person re-identification task, aiming to match pedestrian images between RGB and depth modalities. Its main challenge lies in the significant modality difference between RGB and depth images. Due to the limited research attention on this task, there is a lack of large-scale, high-quality training data, making existing methods struggle to capture effective correlational information between RGB and depth modalities. This paper proposes a novel feature embedding expansion network for RGB-D cross-modal person re-identification. The network introduces perturbations to the embedding of intermediate-layer features to generate multiple diversified embedding features, effectively alleviating the problem of limited training data for RGB-D tasks. Simultaneously, through the incorporation of deformable convolution operations and depth-wise separable convolution operations during the embedding feature generation, the model is encouraged to learn richer scale and channel information from the limited training data. Meanwhile, by controlling the distance between expanded feature embeddings and original feature embeddings for different modalities, we mitigate the significant modality differences. Experimental results on the public benchmark datasets BIWI and RobotPKU demonstrate that our approach outperforms state-of-the-art methods. © 2024 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Bimodal Regression Method for Passenger Flow Prediction in Large Airport Terminals

Bimodal Regression Method for Passenger Flow Prediction in L...

引用

2024 International Annual Conference on Complex Systems and Intelligent science, CSIS-IAC 2024

作者： Li, Wenqiang Zhong, Jinghui School of Computer Science and Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9798331504755

With the rapid development of the civil aviation industry, the number of civil aviation passengers continues to increase. However, it also brings new challenges to the crowd control capability of airports. Predicting the trend of the passen-ger flow is an important way to realize intelligent airport crowd control, and also has profound significance for building a modern national airport system, which is conducive to further improving the service quality and management level. In this paper, we propose an effective bimodal regression method for predicting the passenger flow by utilizing flight schedule information and crowd density information. Experimental results show that the proposed method offers promising performance in terms of prediction accuracy and robustness. © 2024 IEEE.

关键词： Airport buildings

来源：评论

学校读者我要写书评

暂无评论

Coalition-Based Web Server Load Balancing in Software Defined Network 6

Coalition-Based Web Server Load Balancing in Software Define...

引用

6th International Conference on Computational Intelligence and Networks, CINE 2024

作者： Budania, Vijay Tehariya, Sanjay Sharma, Suhana Singh, Atinder Pal Mina, Aman Ahmed, Mushtaq Malaviya National Institute of Technology Department of Computer Science and Engineering Jaipur India

ISBN: (纸本)9798331516796

Software Defined Network(SDN) is a paradigm, which defines new architecture for network management. In traditional networking, the network is managed by dedicated net neg working devices. These devices have tightly coupled control plane and data plane. And generally proprietary in nature. For load balancing, traditional networks use an expensive hardware device. But in the case of SDN, only a new load balancing application is needed to install at the controller. This application uses APIs provided by the controller to build logic for load balancing. Here this paper proposes a game theory-based load-balancing application. It uses concepts of the coalition from cooperative game theory to build the logic of load balancing. The coalition build is based on the hosts connected to a particular OpenFlow switch, i.e. close proximity. The performance of the proposed algorithm is evaluated and compared to a round-robin load balancing scheme under a Mininet emulated environment. Experimental evaluations in a Mininet-emulated environment demonstrate that the proposed method improves throughput by up to 19% compared to the round-robin method under peak loads. Additionally, the proposed method reduces average response time by up to 6%, while also minimizing network congestion and traffic, outperforming the round-robin scheme in overall performance. © 2024 IEEE.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Role of Artificial Intelligence for Noninvasive Height Measurement Applications: A Survey 7

Role of Artificial Intelligence for Noninvasive Height Measu...

引用

7th IEEE Pune Section International Conference, PuneCon 2024

作者： Ruchitha, Inaganti Dhavale, Sunita Defence Institute of Advanced Technology Department of Computer Science and Engineering Pune India

ISBN: (纸本)9798331527822

Height measurement is crucial across various domains including healthcare, ergonomics, security, and forensic analysis. Traditional methods, such as stadiometers, often require cooperation from the subject and can be intrusive, posing significant challenges especially with children, the elderly, or individuals with disabilities. This survey paper addresses the growing need for artificial intelligence (AI) based noninvasive, automated height measurement techniques that can effectively estimate height without physical interaction. In this paper, we examined different state of the art methodologies for height measurement application area, including AI, computer vision (CV), deep learning (DL), depth imaging, and 3D laser scanning. While 3D scanning and depth imaging methodologies provide precise measurements, but they require specialized equipments which leads to additional costs for implementation. Recently, DL and advanced CV models have shown great accuracy in height estimation. Promising solutions for uncooperative subjects can be found by utilizing facial recognition and anatomical traits, and incorporating biometric parameters which can improve prediction accuracy. Despite these advancements, challenges remain with methods requiring multiple images or additional equipment, underscoring the need for more practical and user-friendly solutions. This survey highlights the necessity for tailored approaches to address specific measurement challenges and proposes guidelines for future studies to improve efficiency of noninvasive height estimation technologies. © 2024 IEEE.

关键词： Laser applications

来源：评论

学校读者我要写书评

暂无评论

Nucleus Segmentation with Modified Attention Gate UNET using Sobel Edge detection 3

Nucleus Segmentation with Modified Attention Gate UNET using...

引用

3rd International Conference for Advancement in technology, ICONAT 2024

作者： Sravanthi, Jakkula Bhukya, Raju National Institute of Technology Computer Science and Engineering Telangana Warangal506004 India

ISBN: (纸本)9798350354171

Automated segmentation of nuclei in hematoxylin and eosin (H&E) stained histopathology images is crucial for precise cancer diagnosis and prognosis. These methods enable comprehensive analysis of numerous nuclei within H&E stained histopathology images, offering both qualitative and quantitative insights. However, accurately segmenting nuclei with variable sizes and ambiguous boundaries presents a significant challenge, impacting the reliability of the segmentation process. To tackle this challenge, our research introduces a novel approach integrating edge information extracted from input data into the UNET model, a widely used architecture for image segmentation tasks. By modifying the attention gate mechanism within the UNET model, we aim to prioritize edge features during segmentation. This enhancement is essential for improving the delineation of nuclei boundaries, especially in cases with unclear boundaries, thereby reducing segmentation errors and enhancing overall accuracy. In summary, our study presents an innovative methodology to enhance nuclei segmentation in H&E stained histopathology images. By leveraging edge information and refining the attention mechanism within the UNET model, we aim to address challenges associated with variable-sized nuclei and unclear boundaries, ultimately improving the accuracy of cancer diagnosis and prognosis. © 2024 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Review of Recent Artificial Intelligence Techniques and IOT Applications in Dairy Farms 10

A Comprehensive Review of Recent Artificial Intelligence Tec...

引用

10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Anusree, K. Rajeswari, M. Priyadharshini, C. Karunya Institute of Technology and Science Department of Computer Science and Engineering Tamil Nadu Coimbatore India Sahrdaya College of Engineering and Technology Kerala Kodakara India

ISBN: (纸本)9798350384369

Each and every aspect of daily life has undergone a change thanks to the Internet of Things technology that renders everything intelligent. The wide range of IoT applications has captivated numerous researchers, and IoT enabled dairy farming is being leveraged to undertake innovative studies integrating IoT and Artificial Intelligence (AI) technology. More prospects for intelligent dairy farming are being created by the IoT and data-driven methods. Since the global population is increasing, there is a constant appetite for milk. Developed countries use a greater amount of dairy products than developing nations do. Enhanced technological approaches are required to elevate milk production and meet the escalating demand for dairy products. It is anticipated that a farmer would be able to significantly increase milk output and conquer several traditional farming obstacles with the help of IoT and various AI solutions. This study discusses various difficulties that dairy farmers deal with on every day of their lives. The primary objective of this paper is to undertake a comprehensive review on various Io'T, machine learning(ML) and deep learning(DL) technologies used in the field of smart dairy farming. It also looks into the difficulties and issues that traditional methods encounter as well as their results. Furthermore, the development of an IoT -enabled automated system for dairy farming may benefit further from this evaluation of research. © 2024 IEEE.

关键词： Smart agriculture

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 << < 482 483 484 485 486 487 488 489 490 491 > >>

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：