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

6 篇 会议

馆藏范围

6 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4 篇 工学
- 2 篇 计算机科学与技术...
- 2 篇 软件工程
- 2 篇 生物工程
- 1 篇 机械工程
- 1 篇 光学工程
- 1 篇 电气工程
- 1 篇 电子科学与技术（可...
- 1 篇 信息与通信工程
- 1 篇 交通运输工程
- 1 篇 生物医学工程（可授...
3 篇 理学
- 2 篇 生物学
- 1 篇 系统科学
1 篇 教育学
- 1 篇 教育学
1 篇 医学
- 1 篇 基础医学(可授医学...
- 1 篇 临床医学
- 1 篇 药学(可授医学、理...

主题

1 篇 carpooling probl...
1 篇 allocation algor...
1 篇 time windows
1 篇 embedded systems
1 篇 pickup and deliv...
1 篇 carpooling
1 篇 nonlinear system...
1 篇 estimation of di...
1 篇 delivery problem
1 篇 convolutional ne...
1 篇 stochastic optim...
1 篇 positron emissio...

机构

1 篇 networked object...
1 篇 national school ...
1 篇 sousse universit...
1 篇 university of st...
1 篇 national school ...
1 篇 school of comput...
1 篇 monastir univers...
1 篇 networked object...
1 篇 lab. of networke...
1 篇 lab. networked o...

作者

2 篇 sayadi fatma eza...
1 篇 chelly nizar
1 篇 basly hend
1 篇 fang zhang
1 篇 ibrahim anis bel...
1 篇 ben haj hassine ...
1 篇 mohamed amine za...
1 篇 zayene mohamed a...
1 篇 khemiri randa
1 篇 hend basly
1 篇 bouaafia soulef
1 篇 fangjun kuang
1 篇 y. wang
1 篇 fatma ezahra say...
1 篇 messaoud seifedd...
1 篇 ouni bouraoui
1 篇 z. j. yang
1 篇 mekki hassen

语言

6 篇 英文

检索条件"机构=Lab. Networked Objects Control and Communication Systems"

共 6 条记录，以下是1-10 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：

Alzheimer's Disease Detection Based on Features Level Selection for CNN-SVM Combination

Alzheimer's Disease Detection Based on Features Level Select...

引用

2023 IEEE International Conference on Artificial Intelligence and Green Energy, ICAIGE 2023

作者： Zayene, Mohamed Amine Basly, Hend Sayadi, Fatma Ezahra National School of Engineering School of Sousse Lab. Networked Objects Control and Communication Systems Sousse Tunisia

ISBN: (纸本)9798350325539

Neurodegenerative disease especially dementia are reported as disease that leads to death, Alzheimer's Disease (AD) is kind dementia that cause progressive and irreversible brain disorder loss which leads to death. AD shows no symptoms in its early stages which makes diagnosing it its beginning a challenge and helpful for doctors as they can slow down its progress in its early stages. Computer-aided approaches such as machine learning which come up with several techniques to detect AD by extracting features from the given image data and use them to build a classifier. Recently, a subcategory of machine learning called deep learning has widely been employed to enhance the medical diagnosis by attempting notable performance. In fact, these approaches avoid the tricky manual feature extraction using Convolutional Neural Network (CNN) considered as a reference in the field of computer vision. This paper proposes a combination of machine-deep learning technics for early diagnosis of AD from positron emission tomography (PET). We first train our CNN on PET images to extract the most relevant features, then we select the most appropriate CNN's level from where the features will be extracted, which will be feed in a second step as input to a Support Vector Machine based classifier (SVM). The proposed approach achieves notable results that exceeded the performance obtained by various existing approaches. © 2023 IEEE.

关键词： Positron emission tomography

来源：评论

学校读者我要写书评

暂无评论

An FPGA-SoC based Hardware Acceleration of Convolutional Neural Networks 9

An FPGA-SoC based Hardware Acceleration of Convolutional Neu...

引用

9th IEEE International Conference on Sciences of Electronics, Technologies of Information and Telecommunications, SETIT 2022

作者： Bouaafia, Soulef Messaoud, Seifeddine Khemiri, Randa Sayadi, Fatma Ezahra Monastir University Lab. Electronics and Microelectronics Faculty of Sciences of Monastir Monastir Tunisia Sousse University Lab. Networked Objects Control and Communication Systems National Engineering School of Sousse Sousse Tunisia

ISBN: (数字)9781728184425

ISBN: (纸本)9781728184425

Deep learning has evolved as a discipline that has demonstrated its capacity and usefulness in tackling complicated learning issues as a result of recent improvements in digital technology and the availab.lity of authentic data. Convolutional neural networks (CNNs) in particular have demonstrated their usefulness in image processing and computer vision applications. They do, however, need heavy CPU operations and memory bandwidth, which prevents general-purpose CPUs from attaining desirable performance levels. To boost CNN throughput, hardware accelerators such as application-specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), and graphics processing units (GPUs) have been deployed. FPGAs, in particular, have lately been used to accelerate the development of deep learning networks due to their ability to optimize parallelism and power efficiency. Based on hardware-software architecture, this research provides a CNN acceleration model for video compression applications. Vivado High Level Synthesis is used to accelerate the CNN model in order to develop Intellectual Property (IP) cores. © 2022 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Synchronous system design for a high speed treatment and optimized dynamic power

Synchronous system design for a high speed treatment and opt...

引用

2017 International Conference on Engineering and Technology, ICET 2017

作者： Ben Haj Hassine, Siwar Ouni, Bouraoui Networked Objects Control and Communication Systems Lab National Engineering School of Sousse Sousse University BP 264 Sousse Sousse Tunisia

ISBN: (纸本)9781538619490

In the design of current microelectronic systems, low power is extremely needed since it is the key concern for embedded applications. Besides, a faster treatment is definitely required in a word overshadowed by digital technologies. For that, we propose a new design of synchronous circuit based on a detector avoider block that is intended to optimize two important parameters: power and response time, simultaneously. Our proposed design has been implemented and compared to existing ones. The design results have shown a significant gain in terms of dynamic power as well as in terms of response time compared to existing designs, without negatively influencing other constraints. To further improve the efficiency of our method, the gain has been proved by the physical level. © 2017 IEEE.

关键词： Embedded systems

来源：评论

学校读者我要写书评

暂无评论

Experimental validation of flatness control for path planning and tracking for a quadrotor

Experimental validation of flatness control for path plannin...

引用

2017 International Conference on Engineering and MIS, ICEMIS 2017

作者： Chelly, Nizar Mekki, Hassen Ibrahim, Anis Belhadj Networked Objects Control Communication Systems Lab National School of Engineering Sousse Sousse University Tunisia National School of Engineering Sousse Sousse University Tunisia

ISBN: (纸本)9781509067787

In this paper, we investigates the problem of planning and tracking trajectory for a non linear system which is the quadrotor using the flatness theory. The proposed flatness algorithm is real time implemented. The Experimental results using this solution validate the design control along a pre defined trajectory as well as the response of the AR Drone under disturbances is evaluated. © 2017 IEEE.

关键词： Nonlinear systems

来源：评论

学校读者我要写书评

暂无评论

Alzheimer's Disease Detection Based on Features Level Selection for CNN-SVM Combination

Alzheimer's Disease Detection Based on Features Level Select...

引用

Artificial Intelligence & Green Energy (ICAIGE), IEEE International Conference on

作者： Mohamed Amine Zayene Hend Basly Fatma Ezahra Sayadi Lab. Networked Objects Control and Communication Systems National School of Engineering School of Sousse Sousse Tunisia

关键词：

来源：评论

学校读者我要写书评

暂无评论

An Augmented Estimation of Distribution Algorithm For Multi-Carpooling Problem With Time Window

An Augmented Estimation of Distribution Algorithm For Multi-...

引用

IEEE Vehicular Technology Conference

作者： Fang Zhang Z. J. Yang Y. Wang Fangjun Kuang School of Computer and Communication Engineering Liaoning Shihua University Lab. of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences University of Stuttgart

ISBN: (纸本)9781509016990

A multi-carpooling model is proposed for the multi-vehicle carpooling problem in distributed parallel computing environment. A two-stage stochastic optimization of the estimation of distribution algorithm solves the optimum of the multi-carpooling problem with a carpooling probabilistic matrix. A ridable matrix initiates the carpooling probabilistic matrix, and the carpooling probabilistic matrix continues updating during the optimization. The carpooling model mines efficient and compromised ridesharing routes for shared riders by the optimization iterations. Experimental results indicate that the carpooling model has the characteristics of effective and efficient traffic including shorter waiting time, more passenger load, and less average riding distance.

关键词： Carpooling problem Pickup and delivery problem Estimation of distribution algorithm Stochastic optimization Allocation Algorithm CARPOOLING delivery problem Time windows

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1页 << < 1 > >>

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：