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

14,865 篇 会议
2,216 篇 期刊文献
120 册 图书

馆藏范围

17,201 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

10,213 篇 工学
- 6,826 篇 计算机科学与技术...
- 5,722 篇 软件工程
- 2,962 篇 信息与通信工程
- 1,720 篇 控制科学与工程
- 1,610 篇 电子科学与技术（可...
- 1,595 篇 电气工程
- 1,049 篇 生物工程
- 899 篇 生物医学工程（可授...
- 790 篇 光学工程
- 709 篇 机械工程
- 663 篇 动力工程及工程热...
- 640 篇 仪器科学与技术
- 536 篇 化学工程与技术
- 443 篇 安全科学与工程
- 391 篇 交通运输工程
- 352 篇 材料科学与工程（可...
5,239 篇 理学
- 2,705 篇 数学
- 1,647 篇 物理学
- 1,157 篇 生物学
- 890 篇 统计学（可授理学、...
- 588 篇 系统科学
- 537 篇 化学
2,464 篇 管理学
- 1,543 篇 管理科学与工程(可...
- 1,058 篇 图书情报与档案管...
- 808 篇 工商管理
777 篇 医学
- 677 篇 临床医学
- 629 篇 基础医学(可授医学...
- 399 篇 药学(可授医学、理...
- 335 篇 公共卫生与预防医...
459 篇 法学
- 365 篇 社会学
299 篇 经济学
213 篇 农学
180 篇 教育学
73 篇 文学
42 篇 军事学
11 篇 艺术学
1 篇 历史学

主题

506 篇 accuracy
382 篇 feature extracti...
381 篇 deep learning
376 篇 computational mo...
287 篇 real-time system...
276 篇 support vector m...
253 篇 training
244 篇 internet of thin...
225 篇 optimization
215 篇 predictive model...
215 篇 machine learning
180 篇 computer science
179 篇 computer archite...
174 篇 neural networks
172 篇 wireless communi...
168 篇 reliability
166 篇 wireless sensor ...
163 篇 data mining
163 篇 monitoring
155 篇 convolutional ne...

机构

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

作者

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

语言

16,489 篇 英文
464 篇 其他
181 篇 中文
45 篇 日文
20 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 Technology Engineering"

共 17201 条记录，以下是121-130 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：

Enhancing Mortality Prediction in ICU: A Deep Learning Framework for Multivariate Time Series Classification

Enhancing Mortality Prediction in ICU: A Deep Learning Frame...

引用

2024 International Conference on Integration of Emerging Technologies for the Digital World, ICIETDW 2024

作者： Sathia Bhama, Ponsy R K Sarah R, Roshina Shobia, T.R. Vinothini, R. Anna University Dept. of Computer Technology MIT Campus Chennai India Sri Sairam Institute of Technology Dept. of Computer and Communication Engineering Chennai India

ISBN: (纸本)9798331541170

Relying on human diagnosis is potentially prone to errors, time-consuming and leading to treatment mistakes. Early Intensive Care Unit (ICU) mortality prediction is important for determining which patients are most likely to die and for offering appropriate interventions that will preserve their lives. However, conventional diagnostic approaches often face challenges in fully harnessing the extensive information contained within Electronic Health Record (EHR) data, particularly in capturing the intricate temporal dynamics of patient health. In this research paper, a hybrid model leverages the power of Temporal Convolutional Networks (TCN) in conjunction with Bidirectional Gated Recurrent Units (BiGRU) to effectively capture the complex temporal dependencies present in ICU time series data, before constructing the model, the data is pre-processed by cutting-edge Generative Adversarial Network (GAN)-based imputation techniques to handle missing values within the EHR data. Through this comprehensive framework, the goal is to significantly enhance mortality prediction accuracy, empower clinicians with actionable insights into patient prognosis, and ultimately improve patient outcomes in critical care settings. © 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 Hybrid Approach Using Cryptography and K-Least Significant Bit Steganography Algorithm in Cloud Computing 1

A Hybrid Approach Using Cryptography and K-Least Significant...

引用

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

作者： Goyal, Anshika Gupta, Bhumika VMSB Uttarakhand Technical University Dept. of Computer Science & Engineering Dehradun India G.B. Pant Institute of Engineering & Technology Dept. of Computer Science & Engineering Pauri India

ISBN: (纸本)9798331518578

The exponential growth of communication technologies has broadened the cloud computing ecosystem horizon to meet main communication needs. However, in-parallel upsurge in online attacks has alarmed industries to ensure optimal data security. The combination of steganography and cryptosystems has been recognized as an enhanced security model for data transfer among the main security systems now in use. In this paper, a hybrid approach using cryptography and K- Least Significant Bit Steganography algorithm in Cloud Computing (HYBC-KLSBS-CC) are proposed. Initially, input text data is retrieved from cloud storage and compressed using Huffman Compression Coding (HCC) to reduce data size. The compressed data is then encrypted with a Hybrid Cryptography Algorithm (Hyb-MRFC-ALC), combining Modified Random Fibonacci Cryptography and Asymmetric Lightweight Cryptography to ensure robust encryption. Finally, encrypted data is embedded within an image using the K-Least Significant Bit (KLSB) steganography technique, providing additional layer of security. The proposed method enhances data confidentiality, integrity, and storage efficiency in cloud environments. The proposed HYBC-KLSBS-CC approach attains 26.89%, 29.49% and 18.64% lower PSNR and 26.89%, 29.49% and 18.64% lower MSE when analyzed through existing techniques like data security dependent on cryptography steganography related with OTP procedure and Huffman coding in the cloud environment (CS-OTP-CE), a novel hybrid cryptographic framework for secure data storage in cloud computing: Integrating AES-OTP and RSA with adaptive key management and Time-Limited access control (AES-OTP-RSA-CC) and Crypto-Stegno dependent model for securing medical information on IOMT platform (CS-SMI-IOMT). © 2025 IEEE.

关键词： Cloud platforms

来源：评论

学校读者我要写书评

暂无评论

Exploring the Efficacy of Modified Transfer Learning in Identifying Parkinson’s Disease Through Drawn Image Patterns 2

Exploring the Efficacy of Modified Transfer Learning in Iden...

引用

2nd International Conference on Information and Communication technology, ICICT 2024

作者： Daiyan, Nabil Haque, Md Rakibul Dept. of Computer Science & Engineering Rajshahi University of Engineering & Technology Rajshahi6204 Bangladesh

ISBN: (纸本)9798331508227

Parkinson’s disease (PD) is a progressive neurodegenerative condition characterized by the death of dopaminergic neurons, leading to various movement disorder symptoms. Early diagnosis of PD is crucial to prevent adverse effects, yet traditional diagnostic methods are often cumbersome and costly. In this study, a machine learning-based approach is proposed using hand-drawn spiral and wave images as potential biomarkers for PD detection. Our methodology leverages convolutional neural networks (CNNs), transfer learning, and attention mechanisms to improve model performance and resilience against overfitting. To enhance the diversity and richness of both spiral and wave categories, the training dataset undergoes augmentation to increase the number of images. The proposed architecture comprises three phases: utilizing pre-trained CNNs, incorporating custom convolutional layers, and ensemble voting. Employing hard voting further enhances performance by aggregating predictions from multiple models. Experimental results show promising accuracy rates. For spiral images, weighted average precision, recall, and F1-score are 90%, and for wave images, they are 96.67%. After combining the predictions through ensemble hard voting, the overall accuracy is 93.3%. These findings underscore the potential of machine learning in early PD diagnosis, offering a non-invasive and cost-effective solution to improve patient outcomes. ©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

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

A Deep Learning Approach to Analyze the Relationship Between Gender, Height, Weight, and Basal Metabolic Rate from Face Images 2

A Deep Learning Approach to Analyze the Relationship Between...

引用

2nd International Conference on Power, Electrical, Electronics and Industrial Applications, PEEIACON 2024

作者： Siam, Shykul Islam Chowdhury, S.A.H. Ahmed, Nafi Biswas, Swapneel Rajshahi University of Engineering & Technology Dept. of Electronics & Telecommunication Engineering Rajshahi Bangladesh Ahsanullah University of Science & Technology Dept. of Computer Science & Engineering Dhaka Bangladesh

ISBN: (纸本)9798331517984

In response to existing limitations, a novel convolutional neural network (CNN) model tailored for facial attribute estimation is introduced in this study. The methodology encompasses meticulous data preprocessing techniques, including dataset splitting, resizing, cleaning, augmentation, and cropping, to ensure the integrity of the dataset. Through rigorous real-world testing, remarkable accuracy in predicting gender, height, weight, and basal metabolic rate (BMR) from facial photos is demonstrated by our CNN architecture. Notably, unlike conventional approaches where BMR is directly estimated from facial images, three output neurons are employed by our model to simultaneously predict gender, height, and weight, which are sub-sequently utilized for BMR calculation. A primary contribution is made through the development of a comprehensive methodology that advances the reliability of facial attribute estimation by achieving an outstanding accuracy of 98.50% on our dataset named Face-ete and a commendable accuracy of 88.29% on another dataset. Our model outperforms the second-best model by percentage relative improvement factors of 2.19 and 4.28 in terms of BMR prediction accuracy for the 'Faceere' and the other dataset, respectively. This work represents a significant step forward in the field of facial attribute estimation. © 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

Designing a Graphics Processing Unit for 2D Rendering on FPGA for Educational Purpose 3

Designing a Graphics Processing Unit for 2D Rendering on FPG...

引用

3rd International Conference on Advancement in Electrical and Electronic engineering, ICAEEE 2024

作者： Saha, Rupak Sadad, Nahin Ul Mondal, Md. Nazrul Islam Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798350388282

In this paper, design and implementation of a 2D graphics processing hardware unit using FPGA for educational purpose is presented. We propose a more simple & minimalist GPU architecture, which is flexible and easy to understand than existing industrial GPUs. We present a platform for understanding GPU architecture by implementing of graphics algorithms on FPGA for students to use this in laboratories. Students can be benefited from this work as it can be used as a base understanding tool in terms of GPU architecture. It can also be extended to be used in cross disciplinary applications like 3D rendering, computer vision and signal processing visualisation. This research includes descriptions of hardware realization of 2D rasterization rendering algorithms. Hardware Description Language (HDL) called verilog is utilized in designing the architecture. Xilinx Vivado Design Suite software is used for FPGA implementation, targeting Artix 7 FPGA board, which allows users to comprehend the fundamental ideas of hardware design and their applications in graphics rendering. © 2024 IEEE.

关键词： Graphics processing unit

来源：评论

学校读者我要写书评

暂无评论

From Pixels to Diagnosis: Convolutional Neural Networks in Tuberculosis Screening 6

From Pixels to Diagnosis: Convolutional Neural Networks in T...

引用

6th International Conference on Electrical engineering and Information and Communication technology, ICEEICT 2024

作者： Zihan, Tanvir Mahtab Zami, Abduz Ahmed, Mohiuddin Islam, Rakibul Ahmed, Fahim Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi Bangladesh Uiu Dept. of Cse Dhaka Bangladesh

ISBN: (纸本)9798350385779

Tuberculosis (TB) is a chronic lung disease that constitutes one of the top 10 global causes of death. Timely and precise identification of TB is critical, as untreated cases can pose life-threatening risks. Traditional radiographic interpretation by trained professionals is subjective, time-consuming, and prone to human error. This study proposes an automated deep learning-based approach for TB detection from chest X-ray images, based on EfficientNet-B0 architecture. The Convolutional Neural Network (CNN) extracts discriminative features, allowing it to differentiate between normal and abnormal lung patterns indicative of TB. Our choice of the EfficientNet-B0 architecture played a pivotal role in the success of our TB detection model. Training and evaluation were conducted on three distinct datasets: Tuberculosis (TB) Chest X-ray Database, Shenzhen Hospital CXR Set, and Montgomery County CXR Set. The key breakthrough is attaining an accuracy of 99.29% on the Tuberculosis (TB) Chest X-ray Database and 98.50% on the combined dataset. This study presents a promising approach for automated TB screening using readily available chest X-ray images, potentially improving diagnostic accuracy and efficiency, especially in resource-limited settings. We compared our scores with those of other works and found that ours significantly outperforms them. © 2024 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

To Kill a Mockingbird: Cryptanalysis of an Authenticated Key Exchange Scheme for Drones 15

To Kill a Mockingbird: Cryptanalysis of an Authenticated Key...

引用

15th International Conference on Information and Knowledge technology, IKT 2024

作者： Toghraee, Neda Mala, Hamid Dept. of Information Technology Engineering Faculty of Computer Engineering University of Isfahan Isfahan Iran

ISBN: (纸本)9798331522254

Drones have evolved into sophisticated autonomous systems with a multitude of applications, including military operations, environmental monitoring, traffic oversight, data transmission, package delivery, fire targeting, and film production. As the Internet of Drones (IoD) ecosystem expands, ensuring secure and real-time access for authorized users becomes increasingly vital. User and drone authentication is crucial for this reason. In response to these challenges, Srinivas et al. proposed a lightweight three-factor authentication protocol designed for the IoD. While the authors assert that their protocol is resilient against known cyber threats, our research identifies critical vulnerabilities that challenge this claim. Although this scheme has already been cryptanalyzed in previous studies, in this paper we propose two new attacks on this scheme. Firstly, we present a concrete attack against the perfect forward secrecy of this scheme, and then we show that it is vulnerable to unauthorized access attack by a valid user to an unauthorized area's information. These weaknesses highlight the pressing need for the development of more secure authentication mechanisms in the IoD environment. Moving forward, addressing these vulnerabilities will be essential for fostering trust and ensuring the safe integration of drones into various applications, ultimately contributing to the advancement of IoD technology. © 2024 IEEE.

关键词： Authentication Protocol

来源：评论

学校读者我要写书评

暂无评论

Advancing Ophthalmology through Transfer Learning and Channel-Wise Attention for Retinal Disease Classification 6

Advancing Ophthalmology through Transfer Learning and Channe...

引用

6th International Conference on Electrical engineering and Information and Communication technology, ICEEICT 2024

作者： Islam, Sudipta Progga Alam, Ashraf Ul Rajshahi University of Engineering & Technology Dept. of Computer Science & Engineering Rajshahi6204 Bangladesh

ISBN: (纸本)9798350385779

The global incidence of ocular disorders, which impacts more than 2.2 billion people, requires innovative approaches to ensure early and accurate diagnosis. This paper explores the integration of artificial intelligence (AI) in ophthal-mology, focusing on retinal diseases like cataracts, glaucoma, and diabetic retinopathy. The utilization of AI enables remote examinations and consultations, providing a crucial advantage in early disease detection. This study introduces a comparative analysis of state-of-the-art models, combining pre-trained convolutional neural networks (CNNs) and incorporating a channel-wise attention mechanism for enhanced discriminative ability. The proposed hybrid model, combining EfficientNetBO and Inception V3 with channel-wise attention mechanism, exhibits a remarkable accuracy of 98.13%, outperforming standalone models and other combinations. The findings underscore the efficacy of combined architectures and the integration of attention mechanisms in advancing the classification of retinal diseases. © 2024 IEEE.

关键词： Ophthalmology

来源：评论

学校读者我要写书评

暂无评论

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

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 << < 9 10 11 12 13 14 15 16 17 18 > >>

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：