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

20,200 篇 会议
163 篇 期刊文献
80 册 图书
3 篇 学位论文

馆藏范围

20,446 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

12,718 篇 工学
- 8,282 篇 计算机科学与技术...
- 4,996 篇 软件工程
- 4,960 篇 信息与通信工程
- 4,631 篇 电气工程
- 1,443 篇 控制科学与工程
- 1,317 篇 电子科学与技术（可...
- 1,214 篇 光学工程
- 897 篇 生物医学工程（可授...
- 867 篇 机械工程
- 824 篇 仪器科学与技术
- 811 篇 生物工程
- 318 篇 网络空间安全
- 287 篇 交通运输工程
- 280 篇 安全科学与工程
- 277 篇 化学工程与技术
- 244 篇 动力工程及工程热...
- 187 篇 建筑学
- 178 篇 土木工程
4,646 篇 理学
- 2,146 篇 数学
- 2,061 篇 物理学
- 874 篇 生物学
- 667 篇 统计学（可授理学、...
- 522 篇 系统科学
- 324 篇 化学
1,519 篇 医学
- 1,405 篇 临床医学
- 383 篇 基础医学(可授医学...
- 269 篇 药学(可授医学、理...
1,361 篇 管理学
- 820 篇 管理科学与工程(可...
- 612 篇 图书情报与档案管...
- 208 篇 工商管理
204 篇 法学
136 篇 农学
78 篇 经济学
69 篇 军事学
63 篇 教育学
40 篇 文学
24 篇 艺术学
1 篇 哲学
1 篇 历史学

主题

1,117 篇 image segmentati...
1,059 篇 signal processin...
1,059 篇 image coding
1,007 篇 image processing
987 篇 internet of thin...
952 篇 feature extracti...
826 篇 image reconstruc...
631 篇 internet
553 篇 signal processin...
495 篇 signal to noise ...
476 篇 image edge detec...
474 篇 deep learning
456 篇 training
423 篇 image color anal...
400 篇 cameras
397 篇 robustness
391 篇 image enhancemen...
306 篇 image resolution
292 篇 image recognitio...
289 篇 visualization

机构

58 篇 school of inform...
39 篇 university of sc...
37 篇 signal processin...
29 篇 microsoft resear...
27 篇 university of ch...
26 篇 institute of sig...
26 篇 signal processin...
25 篇 center for signa...
24 篇 university of el...
23 篇 school of electr...
21 篇 ieee
21 篇 college of big d...
20 篇 school of cyber ...
20 篇 department of si...
20 篇 school of inform...
20 篇 signal and infor...
20 篇 school of electr...
19 篇 hsch darmstadt d...
19 篇 peng cheng labor...
19 篇 harbin institute...

作者

31 篇 li zhuo
27 篇 zhuo li
25 篇 sridharan sridha
23 篇 yang yang
23 篇 r.m. mersereau
20 篇 jing zhang
20 篇 wei li
20 篇 gabbouj moncef
19 篇 mansouri majdi
18 篇 zhang lei
18 篇 busch christoph
18 篇 m. gabbouj
17 篇 m.j.t. smith
17 篇 bouzrara kais
17 篇 clinton fookes
17 篇 zhang yan
16 篇 wang lei
16 篇 takahiro ogawa
16 篇 ghassan alregib
15 篇 mellouk abdelham...

语言

20,127 篇 英文
233 篇 其他
75 篇 中文
7 篇 俄文
6 篇 土耳其文
1 篇 西班牙文

检索条件"任意字段=IEEE International Conference on Signal Image Technology and Internet Based Systems"

共 20446 条记录，以下是4871-4880 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：

2021 ieee international conference on Omni-Layer Intelligent systems, COINS 2021

2021 IEEE International Conference on Omni-Layer Intelligent...

引用

2021 ieee international conference on Omni-Layer Intelligent systems, COINS 2021

ISBN: (纸本)9781665431569

The proceedings contain 42 papers. The topics discussed include: baseline features extraction from microelectrode array recordings in an in vitro model of acute seizures using digital signal processing for electronic implementation;task offloading for edge-fog-cloud interplay in the healthcare internet of Things (IoT);TEACHING - trustworthy autonomous cyber-physical applications through human-centered intelligence;quantification of uncertainties in deep learning - based environment perception;D-MQTT: design and implementation of a pub/sub broker for distributed environments;secure cloud control using verifiable computation;on automatic extraction of on-street parking spaces using park-out events data;and a preliminary analysis of hospitalized COVID-19 patients in Alessandria area: a machine learning approach.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Empirical Performance Analysis and Channel Modeling of UAV-Assisted LoRa Networks 30

Empirical Performance Analysis and Channel Modeling of UAV-A...

引用

30th international conference on Electrical Engineering, ICEE 2022

作者： Aghajari, Hossein Ahmadinabi, Sajad Babadegani, Hamed Bakhtiari Soorki, Mehdi Naderi Engineering Faculty Ahvaz Iran

ISBN: (纸本)9781665480871

Long range (LoRa) technology has been widely proposed to empower cost-efficient and scalable communication backbone for the battery-constrained internet of thing (IoT) device. However, the LoRa-based IoT network suffers from a limitation in coverage caused by high signal attenuation due to the terrestrial blockages especially in the urban and suburban environments. To overcome this issue, the use of unmanned aerial vehicles (UAVs) as a flying LoRa gateway to transfer messages from ground LoRa nodes to the cellular base station is proposed. Thus, it is of great interest to accurately model the propagation channel and performance analysis of UAV-Assisted LoRa network based on real measurements. In this paper, a UAV-Assisted LoRa Network is empirically implemented and analyzed. First, LoRa node and gateway are designed and practically implemented using LoRa Ra-02 module, Arduino Uno board, and SIM800l GSM module. Then, the LoRa gateway is mounted over DJI Phantom 4 Pro drone to have a flying LoRa gateway. In this UAV-assisted LoRa Network, the LoRa node sends data to the LoRa gateway over LoRa links, and then LoRa gateway sends data over cellular link to the server. The UAV-Assisted LoRa Network is set up over the campus of Shahid Chamran University of Ahvaz. For this network, different experiment scenarios including line-of-sight (LoS) or none-LoS (NLoS) links and ground or flying LoRa gateway are considered. Following the real-world measurement in these scenarios, the channel model parameters of LoRa links between flying or ground gateway and node are empirically estimated. Our results show that the path loss exponent of LoS LoRa link is 2.57 for ground LoRa gateway, while the LoS path loss exponent of LoRa link decreases to 1.65 for 80m-height flying LoRa gateway. Moreover, our practical analysis shows that the useful coverage area of network rapidly increases when the flying LoRa gateway is used instead of ground LoRa one. © 2022 ieee.

关键词： internet of things

来源：评论

学校读者我要写书评

暂无评论

A Multi-station signal Sorting Method based on TDOA Grid Clustering 6

A Multi-station Signal Sorting Method Based on TDOA Grid Clu...

引用

6th international conference on signal and image Processing, ICSIP 2021

作者： Zhao, Zihao Zhang, Huaguo Gan, Lu University of Electronic Science and Technology Department of Information Engineering Chengdu China Yibin Institute of UESTC Yibin China

ISBN: (纸本)9780738133737

As the electromagnetic environment of the modern battlefield becomes more complex and the radar technology develops rapidly, radar signal sorting has faced a lot of difficulties. A new method of signal sorting based on multistation cooperative and TDOA grid clustering is proposed in this letter. This new method estimates TDOA from pulse sequences received by several stations by TDOA grid clustering. Compared to other pulse description words (PDW) such as PRI, CF, DOA and other parameters, TDOA is a more stable and easily obtained parameter. Therefore, this method can solve the problem that the traditional methods have poor effects on complex signals. Theoretical analysis and simulations show that this method has strong robustness and wide applicability, it shows high accuracy for complex pulse sorting and has a good sorting effect in case of a high amount of losing pulses. © 2021 ieee.

关键词： Time difference of arrival

来源：评论

学校读者我要写书评

暂无评论

internet of Things Attack Group Identification Model Combined with Spectral Clustering 21

Internet of Things Attack Group Identification Model Combine...

引用

21st ieee international conference on Communication technology, ICCT 2021

作者： Fu, Chen Rui, Yu Wen-Mao, Liu School of Computer Science Central University of Finance and Economics Beijing102206 China NSFOCUS Technologies Group Co. Beijing100089 China

ISBN: (纸本)9781665432061

In order to solve the problem that the ordinary intrusion detection model cannot effectively identify the increasingly complex, continuous, multi-source and organized network attacks, this paper proposes an internet of Things attack group identification model to identify the planned and organized attack groups. The model takes the common attack source IP, target IP, time stamp and target port as the characteristics of the attack log data to establish the identification benchmark of the attack gang behavior. The model also combines the spectral clustering algorithm to cluster different attackers with similar attack behaviors, and carries out the specific image analysis of the attack gang. In this paper, an experimental detection was carried out based on real IoT honey pot attack log data. The spectral clustering was compared with Kmeans, DBSCAN and other clustering algorithms. The experimental results shows that the contour coefficient of spectral clustering was significantly higher than that of other clustering algorithms. The recognition model based on spectral clustering proposed in this paper has a better effect, which can effectively identify the attack groups and mine the attack preferences of the groups. © 2021 ieee.

关键词： internet of things

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of Adaptive Filter and Machine Learning Algorithms for Heart Rate Estimation Using PPG signal 3

Performance Analysis of Adaptive Filter and Machine Learning...

引用

3rd international conference on Information and Communication technology for Development for Africa (ICT4DA)

作者： Yigzaw, Tsion Gared, Fikreselam Kassaw, Amare Bahir Dar Univ Bahir Dar Inst Technol Bahir Dar Ethiopia

ISBN: (纸本)9781665436663

Photoplethysmography (PPG) signal provide advanced and simple ways for estimating heart rate (HR) information as an unremarkable system on wearable devices. In this paper, we analyze the performance of adaptive filter and machine learning (ML) algorithms for estimation of HR during physical activity. Three cascades recursive least square (RLS) and cascades normalized least mean square (NLMS) adaptive filters are developed and combined using convex combination scheme to reduce motion artifacts (MA) from the recorded PPG signal. Then, ML based spectral tracking algorithms is applied, to locate the spectral peak corresponding to HR. Four different supervised ML algorithms (Support Vector Machine, Decision Tree, K- Nearest Neighbor and Logistic Regression) are examined to track the spectral peaks and the decision tree out performs all three algorithms with an accuracy of 98.96%. Experimental results on the PPG datasets including 23 subjects used in the 2015 ieee signal processing cup showed that the proposed approach has a very good performance by achieving an average absolute error (AAE) of 1.98 beats per minute (BPM) and the personal correlation coefficient of 0.9899. AAE result proved that the proposed method provides accurate HR estimation performance in comparison with other existing works.

关键词： Adaptive filter HR MA ML PPG

来源：评论

学校读者我要写书评

暂无评论

Research on image Classification of Lightweight Convolutional Neural Network 2

Research on Image Classification of Lightweight Convolutiona...

引用

2nd ieee international conference on Big Data, Artificial Intelligence and internet of Things Engineering, ICBAIE 2021

作者： Yuan, Zhengwu Lu, Chenxing Chongqing University of Posts and Telecommunications College of Computer Science and Technology Chongqing China

ISBN: (纸本)9780738131221

Convolutional neural networks are widely used in related tasks in the image field. However, in order to achieve high accuracy, modern convolutional neural networks often contain a large number of hidden layers and training parameters, resulting in a substantial increase in computing costs. Training and deployment of convolutional neural network models require a large amount of computing and storage resources, which is difficult to apply to smart mobile devices, embedded devices and IoT devices. In order to make the network more efficient, the existing lightweight convolutional neural networks often have shallow depth and limited feature extraction capabilities, and there is still a large room for improvement in accuracy. In response to these problems, a lightweight convolution unit is designed to replace the traditional convolution operation in this paper, and a lightweight convolutional neural network LCUNet based on the VGG-16, VGG-19 and ResNet network structure are designed. These networks are used to do image classification experiments on CIFAR-10 dataset. The experimental results show that the lightweight convolutional neural networks designed in this paper are better than the current efficient lightweight convolutional neural network MobileNet series and ShuffleNet series, and the amount of parameters and calculations are more less. © 2021 ieee.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Imbalanced correction method for power systems transient stability assessment based on the imbalance degree of image samples 23

Imbalanced correction method for power systems transient sta...

引用

Proceedings of the 2023 international conference on Power, Communication, Computing and Networking Technologies

作者： Jianxin Lin Yufei Lu College of Electrical Engineering and Automation Fuzhou University China

ISBN: (纸本)9781450399951

In the transient stability assessment, machine learning based model has the problem that sample imbalance makes the model have a certain degree of evaluation tendency. From the loss function of the machine learning based model, it is found that the fitting degree to various samples after training can be mirrored by the loss function value of the samples. Therefore, a cost-sensitive strategy based on the imbalance degree of the loss function is proposed. Firstly, the machine learning based model is trained to obtain the mean value of loss functions of various samples. Then, the sample imbalance degree is calculated by the mean ratio of the loss function of unstable samples to that of stable samples. After that, the loss function is modified by the sample imbalance degree combined with the cost-sensitive strategy. Finally, to remedy the assessment inclination, the model is trained once again. When compared to conventional approaches, the suggested method comprehensively considers the impact of the imbalance in quantity and spatial distribution of samples. This model achieves higher global accuracy and greater corrective effect. Simulation findings on ieee 39-bus and ieee 145-bus systems are used to confirm the usefulness of the suggested strategy.

关键词： CNN deep learning graph signal sample imbalance transient stability assessment

来源：评论

学校读者我要写书评

暂无评论

Baby-Guard: An IoT-based Neonatal Monitoring System Integrated with Smart Textiles 7

Baby-Guard: An IoT-based Neonatal Monitoring System Integrat...

引用

7th ieee international conference on Smart Computing (SMARTCOMP)

作者： Cay, Gozde Solanki, Dhaval Ravichandran, Vignesh Hoffman, Laurie Laptook, Abbot Padbury, James Salisbury, Amy L. Mankodiya, Kunal Univ Rhode Isl Dept Elect Comp & Biomed Engn Kingston RI 02881 USA Women & Infants Hosp Rhode Isl Pediat Providence RI USA Virginia Commonwealth Univ Sch Nursing Richmond VA USA

ISBN: (纸本)9781665412520

A rising number of preterm babies demands innovative solutions to monitor them in the Neonatal Intensive Care Unit (NICU) continuously. NICU monitors various kinds of vital signs. Among them, there is a strong demand for an accurate and sophisticated technology to monitor respiration rate (RR) and detect critical events such as apnea. Existing solutions for RR monitoring either rely on the indirect measurements from thoracic impedance or other invasive techniques posing discomfort and risk of infections to babies. Also, multiple wire loops lying around babies hinder the delivery of parental and clinical care. Motivated by this need, we have designed an internet-of-Things (IoT) based smart textile chest belt called "Baby-Guard" to monitor RR and detect apnea. The Baby-Guard is a neonatal wearable system consisting of a sensor belt, a wearable embedded system, and an edge computing device. The sensor belt consists of textile-based pressure sensors and an Inertial Measurement Unit (IMU). The wearable system consists of a microcontroller equipped with wireless connectivity and power management. The edge computing device (ECD) connects with the wearable system through an MQTT networking architecture. ECD hosts signal processing and computing services to extract RR and detect apnea. We conducted simulation experiments using a high-fidelity, programmable NICU baby mannequin. We found an average error of 0.89 BrPM in breathing rate and similar to 97 percent accuracy in apnea detection. Computation and communication latencies were found to be similar to 66 and 22 ms, respectively. The Baby-Guard showed potential to be a wireless infant monitoring system in the NICU settings.

关键词： internet of Things IoT NICU Neonatal Care Health Monitoring Respiration Monitoring Smart Textiles

来源：评论

学校读者我要写书评

暂无评论

Developing a Deep Learning-based Embedded System to Detect Adverse Weather Conditions for Autonomous Vehicles

Developing a Deep Learning-Based Embedded System to Detect A...

引用

ieee international conference on Research, Innovation and Vision for the Future

作者： Khanh-Van H. Ngo Hung K. Nguyen Key Laboratory for Smart Integrated System (SISLAB) VNU University of Engineering and Technology HaNoi VietNam

ISBN: (数字)9798331505073

ISBN: (纸本)9798331505080

In recent years, the development of autonomous vehicles has achieved significant progress thanks to breakthroughs in technology. However, unusual weather conditions such as heavy rain, snowfall, or heavy fog can affect the decision-making process of autonomous vehicles, thereby reducing their operational responsiveness and significantly impacting safety and reliability levels. This paper aims to develop a deep learning-based embedded system to detect and classify weather conditions, enhancing the decision-making capabilities of autonomous vehicles, therefor increasing safety and adaptability. We will experimentally assess the performance of three Convolutional Neural Network (CNN) models: ResNet-50, EfficientNet-B0, and SqueezeNet, deployed on a Raspberry Pi 4. Key tasks include collecting and preprocessing data, training the models using transfer learning, converting the trained models to tflite format and quantizing them to float16, deploying them on an embedded platform and evaluating their performance. Experimental results show that the EfficientNet-B0 model is the most effective. After quantization, the EfficientNet-B0 model can detect adverse weather in real-time with an accuracy rate of 88% on a combined dataset from the DAWM2020 and MCWCD2018 image sets, with an average processing time of 0.196 seconds and a processing speed of 4.8 FPS when running on a Raspberry Pi 4.

关键词： Adaptation models Accuracy Embedded systems Quantization (signal) Decision making Transfer learning Safety Convolutional neural networks Autonomous vehicles Meteorology

来源：评论

学校读者我要写书评

暂无评论

Brain tumor image segmentation method based on M-Unet network 4

Brain tumor image segmentation method based on M-Unet networ...

引用

4th international conference on Pattern Recognition and Artificial Intelligence, PRAI 2021

作者： Ru, Qingjun Chen, Guangzhu Tang, Zaizuo College of Computer Science and Cyber Security Chengdu University of Technology Industrial Internet Center Chengdu China

ISBN: (纸本)9781665413220

Brain tumor image segmentation is a challenging problem in medical image processing. The purpose is to obtain tumor location, size, structure and other information through intelligent processing of medical image data. Accurate brain tumor segmentation algorithm plays an important role in the early diagnosis and treatment planning of tumors. Therefore, this paper proposes a brain tumor segmentation algorithm based on M-Unet network(Multi-scale Unet). This method adds multi-scale convolution modules to the feature fusion part of the original Unet network, so that the network can better extract the multiscale features of the image. At the same time, the cosine annealing learning rate attenuation strategy is used in the training process, so that the network can jump out of the local optimal solution to obtain the best network weight. The results show that the M - Unet network achieves high segment results in MRI image dataset, and the Jaccard coefficient and Dice coefficient of the algorithm reach 0.783 and 0.873 respectively;Compared with the original Unet network, the Jaccard coefficient and Dice coefficient are increased by 2.5% and 4.3% respectively, which shows that M-Unet network can effectively improve the segmentation performance of brain tumor image. © 2021 ieee.

关键词： Magnetic resonance imaging

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 << < 484 485 486 487 488 489 490 491 492 493 > >>

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：