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

31,669 篇 会议
4,984 篇 期刊文献
259 册 图书
1 篇 科技报告

馆藏范围

36,913 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

22,988 篇 工学
- 16,611 篇 计算机科学与技术...
- 13,958 篇 软件工程
- 6,082 篇 信息与通信工程
- 3,590 篇 控制科学与工程
- 2,783 篇 电子科学与技术（可...
- 2,727 篇 电气工程
- 2,462 篇 生物工程
- 2,030 篇 生物医学工程（可授...
- 1,618 篇 光学工程
- 1,402 篇 机械工程
- 1,265 篇 仪器科学与技术
- 1,258 篇 动力工程及工程热...
- 1,058 篇 化学工程与技术
- 879 篇 安全科学与工程
- 742 篇 交通运输工程
11,822 篇 理学
- 6,417 篇 数学
- 3,225 篇 物理学
- 2,699 篇 生物学
- 2,120 篇 统计学（可授理学、...
- 1,412 篇 系统科学
- 1,129 篇 化学
5,972 篇 管理学
- 3,449 篇 管理科学与工程(可...
- 2,818 篇 图书情报与档案管...
- 1,918 篇 工商管理
1,692 篇 医学
- 1,470 篇 临床医学
- 1,379 篇 基础医学(可授医学...
- 906 篇 药学(可授医学、理...
- 702 篇 公共卫生与预防医...
1,087 篇 法学
- 881 篇 社会学
682 篇 经济学
- 682 篇 应用经济学
510 篇 农学
463 篇 教育学
162 篇 文学
78 篇 军事学
42 篇 艺术学
6 篇 哲学
4 篇 历史学

主题

1,116 篇 accuracy
865 篇 feature extracti...
864 篇 computational mo...
728 篇 deep learning
720 篇 training
700 篇 computer science
526 篇 support vector m...
526 篇 real-time system...
516 篇 machine learning
453 篇 predictive model...
428 篇 internet of thin...
363 篇 convolutional ne...
359 篇 data models
348 篇 computer archite...
340 篇 reliability
314 篇 data mining
311 篇 optimization
289 篇 routing
270 篇 artificial intel...
263 篇 wireless sensor ...

机构

83 篇 institut univers...
82 篇 north-west unive...
80 篇 national centre ...
79 篇 infn sezione di ...
76 篇 infn sezione di ...
76 篇 institute of inf...
74 篇 tno technical sc...
66 篇 università di ca...
65 篇 université de st...
58 篇 dept. of informa...
58 篇 nikhef national ...
56 篇 dept. of compute...
55 篇 dept. of compute...
55 篇 dept. of informa...
52 篇 school of automa...
52 篇 leiden universit...
49 篇 dept. of compute...
44 篇 dept. of compute...
43 篇 dept. of electri...
42 篇 infn lnf via enr...

作者

86 篇 ferrara g.
85 篇 ardid m.
84 篇 calvo d.
84 篇 gal t.
84 篇 bozza c.
83 篇 chen a.
80 篇 kalekin o.
79 篇 díaz a.f.
79 篇 boumaaza j.
73 篇 coleiro a.
72 篇 gozzini s.r.
68 篇 huang f.
64 篇 dallier r.
54 篇 anguita m.
51 篇 kulikovskiy v.
44 篇 del burgo r.
41 篇 benoit d.m.
41 篇 eddymaoui a.
40 篇 gagliardini s.
40 篇 labalme m.

语言

34,922 篇 英文
1,554 篇 其他
329 篇 中文
63 篇 日文
45 篇 朝鲜文
2 篇 德文
2 篇 斯洛文尼亚文
1 篇 法文
1 篇 葡萄牙文

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

共 36913 条记录，以下是231-240 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：

Optimizing Human Activity Recognition for Precision in Yoga Practice Analysis 8

Optimizing Human Activity Recognition for Precision in Yoga ...

引用

8th IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics, DISCOVER 2024

作者： Salian, Supriya Preethi Salian, K. Rodrigues, Maria Viola Ritesh Muhammed Elham, P.N. Mannan, Mohammed Abdul St. Joseph Engineering College Vamanjoor Dept. of Computer Science and Engineering Mangaluru India Dept. of Information Science and Engineering Udupi India

ISBN: (纸本)9798350350593

The proposed system on enhancing human activity recognition in yoga presents an innovative solution using advanced technologies to accurately and quickly analyze data of yoga poses. Through meticulous data collection and preprocessing, including noise removal, normalization, and handling missing data, the system ensures a clean and standardized dataset. Pose estimation algorithms contribute to accurately mapping the body's posture, extracting essential features like joint angles and body orientation. The features form the basis for a powerful machine learning model, trained on a labelled dataset and employing neural networks, enabling the system to recognize yoga poses with remarkable precision. The study embraces an iterative enhancement process, continuously refining the model based on feedback and performance metrics, ensuring ongoing improvements in accuracy. Ultimately, the proposed system represents a cutting-edge solution for advancing human activity recognition in yoga, providing practitioners with real- time feedback and guidance, fostering improved techniques, and enhancing the overall yoga experience. © 2024 IEEE.

关键词： Mapping

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Driven Cloud Intrusion Detection: Internet of Things and Cloud Networks 1

Deep Learning-Driven Cloud Intrusion Detection: Internet of ...

引用

1st International Conference on Advances in computer science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Moon, Iffath Tanjim Islam Mondal, Md. Nazrul Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798331518578

In this paper, we have utilized deep learning approaches to detect cloud intrusion for the Internet of Things (IoT). The emerging growth of IoT and cloud environments has revolutionized many industries by allowing real-time data sharing and storage. Cloud platforms offer the essential infrastructure for managing the massive volumes of data produced by IoT devices. However, due to several flaws, including insufficient encryption, insecure APIs, and weak authentication, intruders can exploit the vulnerabilities to interrupt services and obtain unauthorized access. Therefore, deep learning can be an effective solution to detect cloud intrusion in IoT. In this research, we have developed individual convolutional neural network (CNN) and long short-term memory (LSTM) models, along with a hybrid CNN-LSTM model for multiclass classification and binary classification to detect cloud intrusion. In addition, we have examined which models perform the best for cloud intrusion detection for IoT among the individual and hybrid models. The proposed models are effective in detecting cloud intrusion, as CNN can extract spatial features, and LSTM can capture temporal dependencies from network traffic data. Furthermore, we have utilized one of the most recent and comprehensive datasets for IoT, the ToN-IoT dataset, containing real-world data. In multiclass classification, the hybrid CNN-LSTM has given the best performance, achieving an accuracy of 97.65%, precision of 97.72%, recall of 97.65%, f1 score of 97.67%, and AUC of 99.93%. In binary classification, all CNN, LSTM, and hybrid CNN-LSTM have demonstrated high performance, where LSTM has achieved the highest accuracy of 99.97%. Moreover, we have evaluated the performance of multiclass classification for detecting nine distinct kinds of attacks. In this instance, CNN has shown better performance in detecting backdoor attacks. Thus, this research can make the IoT platform more secure by efficiently detecting cloud intrusion. © 2025

关键词： Network intrusion

来源：评论

学校读者我要写书评

暂无评论

Approaches for Identifying Suicide Ideation in Social Media Texts: Comprehensive Review 3

Approaches for Identifying Suicide Ideation in Social Media ...

引用

3rd IEEE World Conference on Applied Intelligence and Computing, AIC 2024

作者： Sonawane, Jayshri Suresh Jain, Dinesh Sage University Dept. of Computer Science and Engineering Indore India

ISBN: (纸本)9798350384598

In contemporary society, Suicide has become a notable concern within the realm of public health. Suicidal ideation (SI) encompasses thoughts about ending one's life. Factors contributing to suicidal thoughts and actions are diverse, ranging from personal life events to enduring emotional distress. We investigate the issue of identifying such ideation on Twitter, emphasizing the usefulness of a collection of characteristics taken from the literature as well as the function of discussion context in this process. Numerous machine learning algorithms have been put forth to identify SI from internet channels, but because feature engineering and classification techniques are still lacking, the accuracy of these algorithms is still low. Therefore, by using novel deep learning and natural language processing-based feature engineering technique accuracy can be increased. © 2024 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

KoDialogBench: Evaluating Conversational Understanding of Language Models with Korean Dialogue Benchmark 30

KoDialogBench: Evaluating Conversational Understanding of La...

引用

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Jang, Seongbo Lee, Seonghyeon Yu, Hwanjo Dept. of Computer Science and Engineering POSTECH Pohang Korea Republic of

ISBN: (纸本)9782493814104

As language models are often deployed as chatbot assistants, it becomes a virtue for models to engage in conversations in a user's first language. While these models are trained on a wide range of languages, a comprehensive evaluation of their proficiency in low-resource languages such as Korean has been lacking. In this work, we introduce KoDialogBench, a benchmark designed to assess language models' conversational capabilities in Korean. To this end, we collect native Korean dialogues on daily topics from public sources, or translate dialogues from other languages. We then structure these conversations into diverse test datasets, spanning from dialogue comprehension to response selection tasks. Leveraging the proposed benchmark, we conduct extensive evaluations and analyses of various language models to measure a foundational understanding of Korean dialogues. Experimental results indicate that there exists significant room for improvement in models' conversation skills. Furthermore, our in-dept. comparisons across different language models highlight the effectiveness of recent training techniques in enhancing conversational proficiency. We anticipate that KoDialogBench will promote the progress towards conversation-aware Korean language models. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

The Development of a Digital Forensic Framework for Ease of Forensic Analysis 12

The Development of a Digital Forensic Framework for Ease of ...

引用

12th International Symposium on Digital Forensics and Security, ISDFS 2024

作者： Suvarna, Dhruv Km, Mahesh Gupta, Mahika Gabburi, Sonal Honnavalli, Prasad Vm, Sapna Pes University Dept. of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798350330366

With the growing use of digital devices and technologies, the volume of digital forensic evidence in need of analysis also increases. This results in a need for more effective methods to conduct analysis of this evidence in an investigation. This paper discusses the development of a framework for digital forensic processes. The framework will utilize various tools and techniques to enhance the process of collecting, analyzing, and preserving digital evidence. A survey of existing digital forensic tools, including FTK Imager, Autopsy, and The Sleuth Kit was conducted to help identify various pain points faced by investigators throughout the forensic lifecycle. Based on this study, a framework for the analysis of storage data and memory dumps in digital forensics is proposed, incorporating industry best practices and tools such as The Sleuth Kit and Volatility, enhancing ease of use, and thereby promoting more accurate resolutions. © 2024 IEEE.

关键词： Digital forensics

来源：评论

学校读者我要写书评

暂无评论

Real-Time Object Detection with IOT Using a Smart Cart 18

Real-Time Object Detection with IOT Using a Smart Cart

引用

18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024

作者： Omer, Muhammad Ali, Sardar Jaffar Raza, Syed Muhammad Le, Duc-Tai Choo, Hyunseung College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Sungkyunkwan University Dept. of Computer Science and Engineering Suwon Korea Republic of Sungkyunkwan University Dept. of AI System Engineering Suwon Korea Republic of Sungkyunkwan University Dept. of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798350331011

With Industry 4.0's technological advancements, the convenience and affordability of Artificial Intelligence (AI) and IoT have increased. However, customers still face long waiting times in payment queues during the smart shopping experience. Current solutions rely on expensive sensor-based RFIDs or simple barcodes, making them impractical and limited in scalability. This paper proposes an economically smart solution with two cameras on NVIDIA JETSON NANO for realtime object monitoring and automated shopping. Communication between modules is facilitated by TCP/IP and HTTP protocols. By utilizing the YOLO v7, real-time monitoring is achieved. This innovative approach revolutionizes the customer experience by providing a seamless interface and time-saving features. Additionally, it offers potential integration with e-commerce businesses and payment gateways, further enhancing the overall customer and vendor experience. © 2024 IEEE.

关键词： Graphical user interfaces

来源：评论

学校读者我要写书评

暂无评论

Breast Cancer Detection Based on Histopathological Images Using Vision Transformers

Breast Cancer Detection Based on Histopathological Images Us...

引用

2024 International Conference on computer and Applications, ICCA 2024

作者： Alkhater, Rozah Hassan M. Al-Maadeed, Somaya Saleh, Moutaz Akbari, Younes Qatar university Dept. Computer Science and Engineering Doha Qatar

ISBN: (纸本)9798350367560

Breast cancer is a prevalent and potentially fatal malignancy in women, requiring continual improvements in diagnostic techniques. In order to help medical personnel accurately detect dangerous tumors, automated medical image analysis is essential. This paper presents a unique breast cancer detection model that makes use of deep learning and transfer learning approaches in order to improve the accuracy of diagnostics. The pre-trained ViTb-32 model is fine-tuned on a pre-processed dataset to produce cutting-edge results. The model was trained with a public histopathologic breast cancer dataset. The dataset is pre-processed to resize the images and normalize them to enhance the performance during the training and achieve convergence faster. The ViTb-32 model is optimized by fine-tuning the hyperparameters to achieve the best possible accuracy. The proposed model achieves an accuracy rate of 96.92%. The application of this paradigm in the clinical setting has the potential to improve patient outcomes by facilitating early detection and timely intervention, which could reduce the mortality rate of breast cancer patients by detecting the disease at an early stage. © 2024 IEEE.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Deep Dive into Predictive Modeling for Autism Spectrum Disorder using Facial Features and Machine Learning

Deep Dive into Predictive Modeling for Autism Spectrum Disor...

引用

2024 International Conference on Communication, Computing and Internet of Things, IC3IoT 2024

作者： Bhat, Chaitra Goutham, Gagan Bannur, Charvi Kakarla, Sada Mamatha, H.R. Pes University Dept. Of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798350352689

Autism Spectrum Disorder is a neuro-development behavioural disorder that is classified as a chronic disability leaving individuals unable to accurately grasp their environment and can lead to limited development of communication skills, thinking and other social skills. Prediction of ASD using video recordings is an open-ended critical problem in machine learning to facilitate the process of early intervention which requires high computational resources. This research aims to predict ASD in children using videos by extracting features and converting them into a binary classification problem thereby eliminating the need for high computational resources. This research postulates a study of machine learning techniques like Logistic Regression, Decision Trees and Neural Networks in comparison for the prediction of ASD as well as a novel approach to reduce the computational requirements for the analysis of videos. This research also addresses the lack of publically available video datasets for the analysis of Autism. The highest accuracy metric for the models was using the Neural Network architecture closely followed by the Decision Tree Classifier which yielded accuracies of 99.8% and 99.65% respectively. In this article, we offer an overview of predicting Autism Spectrum Disorder whilst focusing on the importance of video datasets. © 2024 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Systematic Analysis of Underwater Image Dehazing and Object Detection 6

Systematic Analysis of Underwater Image Dehazing and Object ...

引用

6th Asia Symposium on Image Processing, ASIP 2024

作者： Ghei, Anushka Krishnan, Dhriti Rajesh Santhosh, Gautam Natarajan, S. PES University Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350376159

Dehazing underwater images is crucial for several underwater applications, including marine biology, exploration, and monitoring. Because of colour distortion, light attenuation, and scattering, underwater imaging presents particular difficulties. This research presents a systematic survey on using transformers and different Generative Adversarial Networks (GANs) for dehazing underwater photos. This survey study looks into transformer-based models, analyzes GAN designs (CycleGAN, Pix2Pix, and UWGAN) in detail, and compares them using a range of metrics, such as Mean Squared Error (MSE), Structural Similarity Index Measure (SSIM), Frechet Inception Distance (FID), and F1-score. Further analysis was carried out using CLAHE on the best-performing models. Our findings emphasize the benefits and drawbacks of the different designs that were employed as well as prospective directions for further study and advancement. © 2024 IEEE.

关键词： Underwater photography

来源：评论

学校读者我要写书评

暂无评论

Knee Osteoarthritis detection and classification using a customized CenterNet with DenseNet201 3

Knee Osteoarthritis detection and classification using a cus...

引用

3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Shirisha, N. Shilpa, K. Meghana, C.H. Rahman, Mohammed Abdul MLR Institute of Technology Dept. of Computer Science and Engineering Hyderabad India MLR Institute of Technology Dept. of Computer Science and Engineering Nalgonda India

ISBN: (纸本)9798331523893

Knee osteoarthritis (KOA) is a prevalent joint disorder diagnosed using imaging modalities like MRI, CT scans, and X-rays, with X-rays being the most cost-effective. Early detection is crucial for effective management. This study presents an automated deep learning approach to detect and classify KOA severity based on the Kellgren-Lawrence (KL) grading system using single posteroanterior standing knee X-ray images. Utilizing the Osteoarthritis Initiative dataset, we employed transfer learning to fine-tune DenseNet-201, enhancing model performance. Additionally, knowledge distillation was applied to reduce computational complexity while maintaining accuracy. Our model achieved over 95% accuracy on both testing and cross-validation datasets, outperforming existing methods. This approach offers a reliable tool for early KOA diagnosis and grading, potentially aiding clinical decision-making © 2025 IEEE.

关键词： Diagnostic radiography

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 << < 20 21 22 23 24 25 26 27 28 29 > >>

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：