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

10,832 篇 会议
2,083 篇 期刊文献
67 册 图书

馆藏范围

12,982 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

8,003 篇 工学
- 4,804 篇 计算机科学与技术...
- 4,038 篇 软件工程
- 2,155 篇 信息与通信工程
- 1,725 篇 控制科学与工程
- 1,394 篇 电气工程
- 1,393 篇 电子科学与技术（可...
- 740 篇 机械工程
- 734 篇 生物工程
- 665 篇 生物医学工程（可授...
- 610 篇 光学工程
- 607 篇 仪器科学与技术
- 525 篇 动力工程及工程热...
- 464 篇 化学工程与技术
- 349 篇 交通运输工程
- 315 篇 安全科学与工程
- 301 篇 建筑学
- 281 篇 材料科学与工程（可...
- 273 篇 土木工程
4,294 篇 理学
- 2,275 篇 数学
- 1,414 篇 物理学
- 782 篇 生物学
- 696 篇 统计学（可授理学、...
- 602 篇 系统科学
- 441 篇 化学
1,770 篇 管理学
- 1,207 篇 管理科学与工程(可...
- 651 篇 图书情报与档案管...
- 573 篇 工商管理
536 篇 医学
- 454 篇 临床医学
- 420 篇 基础医学(可授医学...
- 278 篇 药学(可授医学、理...
278 篇 法学
211 篇 农学
209 篇 经济学
123 篇 教育学
53 篇 文学
32 篇 军事学
12 篇 艺术学
2 篇 哲学
1 篇 历史学

主题

263 篇 feature extracti...
246 篇 accuracy
200 篇 computational mo...
197 篇 deep learning
178 篇 predictive model...
177 篇 real-time system...
155 篇 support vector m...
154 篇 optimization
144 篇 neural networks
135 篇 machine learning
130 篇 wireless communi...
126 篇 internet of thin...
126 篇 monitoring
114 篇 reliability
114 篇 training
110 篇 wireless sensor ...
104 篇 visualization
103 篇 quality of servi...
101 篇 data mining
97 篇 signal to noise ...

机构

71 篇 dept. of informa...
52 篇 dept. of compute...
51 篇 dept. of electri...
51 篇 dept. of electro...
47 篇 dept. of informa...
39 篇 university of th...
36 篇 dept. of electri...
31 篇 dept. of informa...
27 篇 dept. of control...
26 篇 lovely professio...
26 篇 dept. of informa...
25 篇 dept. of electri...
24 篇 school of automa...
22 篇 institute of inf...
21 篇 ieee
19 篇 delft center for...
19 篇 dept. of control...
18 篇 chitkara univers...
17 篇 dept. of materia...
17 篇 dept. of compute...

作者

26 篇 nasmin jiwani
26 篇 ketan gupta
26 篇 magno michele
26 篇 fotiadis dimitri...
25 篇 jiwani nasmin
21 篇 bin zou
19 篇 logeshwaran j.
18 篇 ye zhang
17 篇 widyawan
16 篇 lo hoi-kwong
16 篇 tom oomen
15 篇 balázs benyó
15 篇 oomen tom
14 篇 chen yen-lin
14 篇 hongyi yu
13 篇 zhang ye
13 篇 loeliger hans-an...
12 篇 horng shi-jinn
12 篇 han ji-hoon
12 篇 masaki yamakita

语言

12,339 篇 英文
271 篇 其他
216 篇 中文
81 篇 日文
81 篇 朝鲜文
1 篇 斯洛文尼亚文

检索条件"机构=Dept. of Control Engineering and Information Technology"

共 12982 条记录，以下是61-70 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：

Wrist Fracture Detection Using Deep Learning

Wrist Fracture Detection Using Deep Learning

引用

2025 IEEE International Students' Conference on Electrical, Electronics and Computer Science, SCEECS 2025

作者： Rafi, Shaik Mahmamad Anuradha, T. Srinivas, Kothapalli S. V. V. R. Velagapudi Ramakrishna Siddhartha Engineering College Dept. of Information Technology Kanuru India

ISBN: (纸本)9798331529833

Effective treatment of wrist bone fractures depends on early and precise identification. The finding shows that disparities in accessing timely emergency services translate into adverse patient outcomes, especially in regions with fewer healthcare facilities and extended distances, mostly rural areas. Distal radial fractures or wrist fractures are among the commonly encountered musculoskeletal injuries and the treatment and subsequent management depend on timely and precise identification of the fracture pattern. This paper discusses a wrist fracture detection scheme using a deep learning approach for diagnosing wrist bone fractures from X-ray images which can close the health disparities due to the lack of adequate early diagnosis. and his team developed the system using DenseNet-201, MobileNetV2, ResNet-50, EfficientNetV2, U-net and Inception V3 architecture because each was selected for a certain use effect patient outcome. Wrist fractures, among the most common musculoskeletal injuries, require early and accurate diagnosis to optimize treatment and rehabilitation. This project presents a deep learning-based system to detect wrist fractures in X-ray images, designed to bridge healthcare inequalities by facilitating early and automated diagnosis. The system integrates DenseNet-201, MobileNetV2, ResNet-50, EfficientNetV2, U-Net, and Inception V3 models, each chosen for specific roles. DenseNet-201, MobileNetV2, and ResNet-50 are classification networks for fracture detection while U-Net is segmentation network to segment fractured areas. Furthermore, the results using EfficientNetV2 and Inception V3 improve diagnostic capability and image *** work compares the pros and cons of each model in terms of accuracy, computational time, and loss and presents recommendations for the most appropriate models for clinical applications in practice. © 2025 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Exploring the Potential of MANETs: A Study on Raspberry Pi and UAV Integration 3

Exploring the Potential of MANETs: A Study on Raspberry Pi a...

引用

3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Archana, B. Mahalakshmi, A. Revathi, K. Ashok Kumar, K. Hema, A.B. Dept. of Computer Science and Engineering Sri Ramakrishna Engineering College Coimbatore India Dept. of Information Technology SNS College of Engineering Coimbatore India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

This research investigates the feasibility of utilizing Mobile Ad Hoc Networks (MANETs) in conjunction with Raspberry Pi-equipped Unmanned Aerial Vehicles (UAV) swarms. The primary objective is to overcome the limitations of traditional communication infrastructures in dynamic and decentralized environments. Specifically, we address the challenge of establishing reliable and efficient communication links within a swarm of UAVs engaged in various applications, including disaster response, military reconnaissance, and environmental monitoring. By integrating Raspberry Pi devices with UAVs, we aim to create a self-organizing communication network that enables seamless data transmission, coordinated swarm operations, and enhanced mission effectiveness. The research explores different synchronization strategies, including master-slave and decentralized approaches, to optimize swarm coordination. Furthermore, we investigate the potential of incorporating advanced technologies such as machine learning, computer vision, and swarm intelligence to further enhance the autonomy, adaptability, and overall performance of the UAV swarm. © 2025 IEEE.

关键词： Mobile ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Machine Learning Methods in Climate Data Extraction and Forecasting

Comparative Analysis of Machine Learning Methods in Climate ...

引用

2025 International Conference on Emerging Technologies for Intelligent Systems, ETIS 2025

作者： Khajgiwale, Parth Ajit Naveen, Atul Jethani, Nishtha Shitole, Ajitkumar International Institute of Information Technology Dept. of Computer Engineering Hinjewadi Pune India

ISBN: (纸本)9798331507541

Climate forecasting plays a critical role in understanding and mitigating the impacts of climate change. Advances in machine learning (ML) have significantly enhanced the accuracy of climate projections, particularly when dealing with large and complex datasets derived from regional climate models (RCMs) and global climate models (GCMs). This study investigates the application of various ML techniques for predicting precipitation based on temperature data extracted from climate datasets. We evaluate a range of regression models, including linear models and advanced ensemble methods such as Gradient Boosting and XGBoost, along with deep learning approaches like Convolutional Neural Networks (CNNs). Through a rigorous evaluation of these models, we focus on their performance as measured by Mean Squared Error (MSE) to identify the most effective techniques for capturing the intricate relationships within climate data. By analyzing existing studies and performance metrics, we aim to provide insights into the capabilities and limitations of these ML models in improving climate predictions. Furthermore, this research highlights the need for incorporating additional climate variables and optimizing model configurations to enhance predictive accuracy in climate forecasting. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Enhancing Multicast Efficiency in Large Cloud Data Center Networks

Enhancing Multicast Efficiency in Large Cloud Data Center Ne...

引用

2024 International Conference on Science, technology, engineering and Management, ICSTEM 2024

作者： Sri Varsini, S.K. Sai Sanjay Raj, J. Swetha, K. Poonkodi, R. Amitha, S. Dept. Information Technology Sri Eshwar College of Engineering Coimbatore India

ISBN: (数字)9798350376913

ISBN: (纸本)9798350376913

The responsibility of updating setup boundaries and communicating board directives to sensor hubs falls under the purview of an information disclosure and spread convention for remote sensor organizations (WSNs). There are two negative aspects to all of the information disclosure and dissemination conventions in use today. They first rely on a concentrated methodology, where information is only accessed by the base station. It is not realistic to construct multi- proprietor multi-client WSNs using such a methodology. Second, opponents can easily launch sendoff attacks to harm the organization because such conventions were not designed with safety in mind. This work offers the DiDrip convention, which is the first safe and distributed information revelation and propagation protocol. It enables the business owners to directly provide information items to the sensor hubs and approve several business clients with different accolades at the same time. Moreover, as our simulated study illustrates, it tackles some reasonable security defects that we have identified. DiDrip's security may be demonstrated by thorough analysis. Additionally, we use DiDrip in an asset-restricted sensor hub experiment to show its high productivity in practical situations. © 2024 IEEE.

关键词： Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

Performance Comparative Analysis of the Accuracy of CNN and RNN in Identifying Photovoltaic Cell Malfunctions

Performance Comparative Analysis of the Accuracy of CNN and ...

引用

2024 International Conference on Science, technology, engineering and Management, ICSTEM 2024

作者： Subhasri, S. Seyad Reesman, T. Dharshini, B. Saranya, D. Priyangababy, D. Dept. of Information Technology Sri Eshwar College of Engineering Coimbatore India

ISBN: (数字)9798350376913

ISBN: (纸本)9798350376913

The goal of this study is to minimize dimensionality in vibration data obtained from rotating machinery through the use of Principal Component Analysis (PCA) for feature extraction, hence enabling prompt failure identification in bearings. After PCA is used to handle the denoised signals, a hybrid deep learning model consisting of CNN and RNN is implemented. This combined method efficiently detects and categorizes different bearing problems by utilizing the temporal dependencies that RNNs learn and the spatial information that CNNs record. This methodology presents a comprehensive framework for proactive bearing health monitoring and maintenance by merging CNN and RNN architectures with PCA-based feature extraction. This might potentially optimize resource allocation and minimize downtime in industrial settings. © 2024 IEEE.

关键词： Principal component analysis

来源：评论

学校读者我要写书评

暂无评论

Predictive Modeling of Student Academic Performance in External Examinations 6

Predictive Modeling of Student Academic Performance in Exter...

引用

6th International Conference on Cybernetics, Cognition and Machine Learning Applications, ICCCMLA 2024

作者： Vennelakanti, Aasritha Varshini Nayakawadi, Rishitha Kodam, Vamshidhar Suryanarayana, G. Sallakunta, Ramya Devulapalli, Indusree Vardhaman College of Engineering Dept. Information Technology Shamshabad Hyderabad India

ISBN: (纸本)9798331505790

In a country like India, where students constitute a major part of the population, there is a need to predict a student's performance. The need for analysing students' academic performance plays an important role in the education sector because the insights gained from this prediction can be used to redesign the curriculum, which helps in meeting the needs of individual students. Educational data mining has been an emerging field to improve educational institutions. Hence, the usage of machine learning techniques in educational data mining has increased rapidly. Accurately predicting students' academic performance is essential for various stakeholders, like instructors, students, and institutions. This study aims to predict a student's performance in external exams using various machine learning techniques. Various metrics, like internal exam scores, previous semester scores, and the attendance of a student, are being considered for predicting GPA in the current semester. Because of the unbalanced nature of the data, it is challenging to develop a high-accuracy model. For this prediction, a variety of machine learning methods can be applied, including Random Forest (RF), K-Nearest Neighbour (kNN), Naïve Bayes (NB), Gradient Boost (GB), Decision Tree (DT), Support Vector Machine (SVM), and Logistic Regression (LR). Ensemble methods can demonstrate high accuracy in model training. By analysing the results produced by our proposed model, valuable insights can be drawn that benefit students', teachers, and educational administrators. © 2024 IEEE.

关键词： Nearest neighbor search

来源：评论

学校读者我要写书评

暂无评论

Poverty Mapping in India using Machine Learning and Deep Learning Techniques

Poverty Mapping in India using Machine Learning and Deep Lea...

引用

2024 Mid-term Symposium on Spatial information to Empower the Metaverse

作者： Srishti Gulecha, R. Muthu Reshmi, K. Rishitha, N. Vani, K. Dept. of Information Science and Technology College of Engineering Guindy Chennai India

Poverty remains a persistent global challenge, that affects millions worldwide and hinders sustainable development goals. Poverty related data is traditionally collected by an on-the-ground household survey which is conducted once in a few years. Unfortunately, in India, the reach of this conventional data collection method has many limitations, and it is costly, time-consuming, and laborious. The study will assist in identifying areas of poverty and also the levels of poverty which will help policymakers in creating policies that will improve such areas. The research leverages a rich variety of data sources which includes satellite imagery, geospatial data, socio-economic surveys and Point of Interest (POI) data. To extract meaningful patterns and correlations within this diverse dataset, various machine learning and deep learning algorithms such as Decision Tree Regressor, Random Forest Regressor, Convolutional Neural Networks (CNNs) and Multi Layer Perceptron (MLP) are employed. With the help of Random Forest Regressor, the study was able to estimate the poverty at village/town level with a R2-score of 0.778. © Author(s) 2024.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Design of a Blockchain-Based Internet of Healthcare System using Cryptography Network Security

Design of a Blockchain-Based Internet of Healthcare System u...

引用

2024 International Conference on Science, technology, engineering and Management, ICSTEM 2024

作者： Bhoomish, R. Vishnuvaradhan, D. Boobalan, E. Vasanthakumar, C. Sudharsan, D.S. Dept. Information Technology Sri Eshwar College of Engineering Coimbatore India

ISBN: (数字)9798350376913

ISBN: (纸本)9798350376913

In this proposed framework, we advocate the joining of blockchain innovation into Electronic Wellbeing Record (EHR) frameworks to resolve major problems encompassing information security, uprightness, and access control in the medical care area. Our structure offers a versatile, secure, and decentralized arrangement, stressing granular access rules, vigorous validation, and cryptographic hashing for information protection and trustworthiness. With the capacity to help dynamic gatherings and work with consistency with medical care guidelines like HIPAA, our framework plans to alter EHR the board, guaranteeing the highest level of secrecy and dependability in taking care of delicate patient records. © 2024 IEEE.

关键词： Network protocols

来源：评论

学校读者我要写书评

暂无评论

I-Flow: Design and evaluation of a wearable uroflowmeter with non-invasive low power bio-impedance sensing 46

I-Flow: Design and evaluation of a wearable uroflowmeter wit...

引用

46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Dheman, Kanika Glahn, Manuel Magno, Michele Eth Zürich Dept. of Information Technology and Electrical Engineering Switzerland

ISBN: (纸本)9798350371499

Urological problems involving lower urinary tract symptoms (LUTS) such as urinary frequency, urgency, nocturia, and urine volume have a significant impact on patient health and quality of life. At present, clinical uroflowmeter tests and a urination frequency-volume chart (FVC) or bladder diary is recommended for monitoring the symptoms and the efficacy of treatment. However, these solutions are intermittent, needing high user compliance, repeated visits to the clinic and are inconvenient, especially for elderly patients. Such limitations lead to misdiagnosis and an inability to personalise treatments. This work proposes i-Flow, a low-power bio-impedance sensing system enabling wearable uroflowmetry. To demonstrate the effectiveness of the proposed solution, a preliminary dataset has been collected from 6 healthy subjects. Furthermore, the dataset acquired with a developed wearable system has been used to design a low-complexity, lightweight bladder voiding measurement algorithm and evaluates the overall hardware-software performance. In addition, repeatability tests on a single subject with multiple voiding instances (n=5) were conducted. The experimental evaluation demonstrates high-performance bladder voiding estimation with the total end volume (TEV) error for multi-subject voiding instances to be 38.4±18 ml. While the TEV error for repeated measures with a single subject was 21.7±15 ml for five voiding instances. The presented system for recording bladder voiding achieves an unobtrusive, comfortable and reliable method for automated recording of the frequency of voiding, the total voided volume and urine flowrate. Thus providing a means of conducting uroflowmetry tests in at-home settings while also maintaining a digital bladder diary devoid of human lapses. Such a system has the ultimate goal of assisting in diagnosis and personalizing treatment of LUTS. © 2024 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

Application to Enhance the Programming Knowledge of Children 6

Application to Enhance the Programming Knowledge of Children

引用

6th International Conference on Advancements in Computing, ICAC 2024

作者： Dissanayake, Anuga Lakpriya, Vishwa Sanjeevan, Mahendran Fahmi, Ahamed Siriwardana, Samanthi E.R. Samaraweera, Mihiri Sri Lanka Institute of Information Technology Dept. of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Dept. of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798331517878

This proposal outlines the development of a comprehensive educational platform aimed at bridging the information technology knowledge gap among Tamil-speaking students in Sri Lanka. The platform is designed to enhance programming skills through personalized quizzes, hands-on projects, and adaptive learning models. The application focuses on two primary components: the first component emphasizes project-based learning and assessments, leveraging advanced Artificial Intelligence models for generating educational content. This model is combined with Retrieval-Augmented Generation, which retrieves relevant external information to refine and tailor the educational content to each student's needs. This component keeps students engaged and challenged at appropriate levels, promoting deeper understanding and practical information technology skills. The second component involves a Level-based IT Fundamental Knowledge Evaluation system, which incorporates machine learning algorithms to predict student performance, recommend customized learning paths, and assess overall technical knowledge. The platform also integrates the OpenAI Application Programming Interface, which provides real-time Tamil translation, making the content more accessible to the target demographic. The platform empowers educators to better address individual student needs with real-time feedback and tailored experiences. Its innovative approach enhances information technology education, equipping Sri Lankan students with essential programming skills to succeed globally. © 2024 IEEE.

关键词： Adversarial machine learning

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 << < 3 4 5 6 7 8 9 10 11 12 > >>

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：