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

18,624 篇 会议
113 篇 期刊文献
16 册 图书

馆藏范围

18,753 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

12,057 篇 工学
- 9,596 篇 计算机科学与技术...
- 5,512 篇 软件工程
- 3,082 篇 电气工程
- 2,954 篇 控制科学与工程
- 2,531 篇 信息与通信工程
- 963 篇 仪器科学与技术
- 941 篇 交通运输工程
- 934 篇 机械工程
- 643 篇 生物工程
- 632 篇 电子科学与技术（可...
- 561 篇 动力工程及工程热...
- 541 篇 生物医学工程（可授...
- 491 篇 安全科学与工程
- 395 篇 石油与天然气工程
- 394 篇 网络空间安全
- 259 篇 光学工程
3,012 篇 管理学
- 2,264 篇 管理科学与工程(可...
- 1,139 篇 图书情报与档案管...
- 868 篇 工商管理
2,970 篇 理学
- 1,521 篇 数学
- 791 篇 生物学
- 506 篇 统计学（可授理学、...
- 491 篇 物理学
- 398 篇 化学
- 393 篇 系统科学
622 篇 医学
- 509 篇 临床医学
- 444 篇 基础医学(可授医学...
- 264 篇 公共卫生与预防医...
333 篇 法学
- 273 篇 社会学
279 篇 经济学
- 274 篇 应用经济学
173 篇 教育学
150 篇 农学
33 篇 文学
31 篇 军事学
12 篇 艺术学

主题

1,144 篇 data acquisition
762 篇 data mining
572 篇 real-time system...
567 篇 data models
444 篇 intelligent syst...
420 篇 conferences
420 篇 big data
407 篇 cloud computing
375 篇 internet of thin...
361 篇 computational mo...
346 篇 monitoring
321 篇 computer archite...
319 篇 sensor systems
308 篇 machine learning
306 篇 control systems
304 篇 deep learning
304 篇 training
299 篇 feature extracti...
287 篇 robot sensing sy...
284 篇 neural networks

机构

49 篇 university of ch...
42 篇 lviv polytechnic...
30 篇 hubei key labora...
25 篇 school of comput...
20 篇 west ukrainian n...
18 篇 beijing key labo...
17 篇 shenzhen institu...
17 篇 chitkara univers...
16 篇 university of el...
15 篇 school of comput...
15 篇 institute of aut...
14 篇 faculty of compu...
14 篇 school of artifi...
14 篇 shenzhen institu...
14 篇 peng cheng labor...
13 篇 ieee
13 篇 college of compu...
12 篇 key laboratory o...
12 篇 beijing univ pos...
12 篇 yeshwantrao chav...

作者

25 篇 anatoliy sachenk...
22 篇 wu xinyu
18 篇 anatoly sachenko
16 篇 a. sachenko
16 篇 liu yang
16 篇 xiong gang
15 篇 chen chen
13 篇 sachenko anatoli...
12 篇 xinyu wu
12 篇 li yang
12 篇 yang yang
12 篇 wang wei
11 篇 zhang tao
11 篇 wang lei
11 篇 li peng
11 篇 li li
11 篇 kurosh madani
11 篇 sachenko a.
11 篇 wu bin
11 篇 iryna turchenko

语言

17,862 篇 英文
824 篇 其他
83 篇 中文
2 篇 西班牙文

检索条件"任意字段=IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems"

共 18753 条记录，以下是1031-1040 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：

Composite Indicators Building Based on Concordant of Expert-Statistical Information Using Biased Ridge Kernel Regression

Composite Indicators Building Based on Concordant of Expert-...

引用

ieee international Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Leonid Lyubchyk Galyna Grinberg Zoia Konokhova Klym Yamkovyi Computer Mathematics and Data Analysis Department National Technical University “Kharkiv Polytechnic Institute” Marketing Department National Technical University “Kharkiv Polytechnic Institute”

The problem of constructing a complex composite indicator based on expert scores and statistical information about particular indicators is considered. A procedure for estimating the parameters of a nonlinear model of a composite indicator based on the method of biased kernel ridge regression is proposed; at the same time, the problem of optimal concordant of expert and statistical information is solved by choosing the appropriate regularization functional. Using the method of Lagrange multipliers, expressions for estimating the parameters of a nonlinear model and a kernel-based model of a composite indicator are obtained. The results of a numerical experiment on the construction of a composite indicator model using real data are presented.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Fingerspelling Classification for Robot Control 22

Fingerspelling Classification for Robot Control

引用

22nd ieee international conference on Industrial Informatics, INDIN 2024

作者： McCready, Kevin Coleman, Sonya Kerr, Dermot Siddique, Nazmul Kerr, Emmett Aloimonos, Yiannis Fermüller, Cornelia School of Computing Engineering and Intelligent Systems Ulster University Londonderry United Kingdom Department of Electronic and Mechanical Engineering Atlantic Technological University Co.Donegal Letterkenny Ireland Institute for Advanced Computer Studies University of Maryland College ParkMD United States

ISBN: (纸本)9798331527471

Improvements to human-robot interaction methods could increase the ease of use of robots in manufacturing environments. Many of these environments are noisy and therefore preclude the use of audio communication between humans or in human-robot interactions. Therefore, this paper proposes using a gesture based communication system for robot control. To that end, the VGG16 and VGG19 convolutional neural network (CNN) structures are used for gesture classification along with 3 datasets of American Sign Language (ASL) fingerspelling images. The model performance is evaluated, and modifications made to their parameters to improve performance, before applying them to robot control tasks. The results show that with parameter tuning, test accuracies of up to, 100% are achievable. © 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

Development and Application of Online Learning System Based on Artificial Intelligence 3

Development and Application of Online Learning System Based ...

引用

3rd ieee international conference on Distributed computing and Electrical Circuits and Electronics, ICDCECE 2024

作者： Gao, Luyun Jinan Preschool Education College Jinan China National University Manila ManilaPH 1008 Philippines

ISBN: (纸本)9798350318609

With the continuous progress of subject knowledge such as Internet and computer technology, as well as the update and improvement of educational models and methods, people's cognition of the concept of artificial intelligence is getting deeper and deeper. Based on the current intelligent background, aiming at various types of problems involved in virtual reality, this paper uses machine automation algorithm to apply online learning system to real life, and studies the optimization of online learning system by artificial intelligence algorithm. After that, this paper also conducts related tests on the performance of the learning system, and the test results show that the resource utilization rate of the system is above 0.7, the data throughput is large, the stability is relatively good, and it is safe enough to run and meet the needs of users. © 2024 ieee.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

Sparse Channel Estimation in Massive MIMO systems Using Compressed Sensing and Neural Networks

Sparse Channel Estimation in Massive MIMO Systems Using Comp...

引用

2024 ieee international conference on intelligent Signal Processing and Effective Communication Technologies, INSPECT 2024

作者： Upadhyay, Deepak Sharma, Kunj Bihari Gupta, Mridul Upadhyay, Abhay Venu, Nookala Graphic Era Hill University Dept. of Computer Science and Engineering Dehradun India Graphic Era deemed to be University Dept. of Computer Science and Engineering Dehradun India ABV Indian Institute of Information Technology and Management Data Science and Quantum Computing Gwalior India

ISBN: (纸本)9798350379525

In this paper, based on compressed sensing and neural networks, we present an intelligent sparse channel estimation technique for Massive MIMO systems. We show that our approach improves considerably the estimation accuracy in terms of Mean Squared Error (MSE) and Normalized Mean Squared Error (NMSE) with respect to classical methods. We demonstrate [Figure: ] that our approach is computationally more efficient, requires less time and resources (memory/disk) compared to the existing literature but for a robustness of performance across distal or low Signal-to-Noise Ratios (SNRs). We also confirm our method exhibits fast convergence and efficiently accommodates a variety of sparsity levels. By visualizing it using heatmaps and ROC curves we show that this method is able to effectively differentiate between signal and noise, asserting our approach as a powerful tool for the contemporary set of problems present in wireless communications. © 2024 ieee.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

An advanced Autoencoder-Based Approach to Anomaly Detection for Video Surveillance systems

An Advanced Autoencoder-Based Approach to Anomaly Detection ...

引用

2024 international conference on Innovative computing, intelligent Communication and Smart Electrical systems, ICSES 2024

作者： Abhiram, G. Nitheesha, Madineni Samatha, Ambati Giriprasad, S. Srm Institute of Science and Technology Department of Electronics and Communication Engineering Kattankulathur Chennai India

ISBN: (纸本)9798331543617

This paper attempts to give a state-of-the-art machine learning anomaly detection in video surveillance using the application of autoencoders. The use of video surveillance ensures safety and security in places like public spaces, office buildings, and homes. However, with the multiple cameras present, monitoring various video feeds is quite demanding and, thus, predisposed to human error or inefficiency when dealing with large environments. The single critical feature that will serve to automate this process pertains to identifying unusual events or behavior. The proposed system relies on an autoencoder neural network model for learning patterns of normal behavior in video streams. The UCSD, a diverse dataset containing surveillance videos, was used to train and test the system. Preprocessing of video data includes frame extraction, resizing, and normalization, followed by feeding into the model. It mainly consists of two parts, namely an encoder that compresses the input data and a decoder that reconstructs the input from the compressed representation. The reconstruction error is then calculated by comparing the original and reconstructed frames. The frames with high reconstruction errors are flagged as containing anomalies. This system shows a high level of accuracy measured in terms of precision and recall. In addition to real-time anomaly detection, the system offers visual feedback to the user regarding which frames are anomalous and can be further inspected. The experiment results demonstrate how the model is robust against vast and complex environments. The proposed system extends a reliable, highly scalable, and flexible solution for smart surveillance, reducing constant human supervision, and improving the speed of response to security threats. More work will go into enhancing the system so that it can better deal with subtler anomalies and generalize to larger datasets for ultimate deployment. © 2024 ieee.

关键词： Visual communication

来源：评论

学校读者我要写书评

暂无评论

Threat Modeling for ML-based Topology Prediction in Vehicular Edge computing Architecture

Threat Modeling for ML-based Topology Prediction in Vehicula...

引用

2023 ieee international conference on Dependable, Autonomic and Secure computing, 2023 international conference on Pervasive Intelligence and computing, 2023 international conference on Cloud and Big data computing, 2023 international conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Doan, Hong Hanh Paul, Audri Adhyas Zeindlinger, Harald Zhang, Yiheng Khan, Sajjad Svetinovic, Davor Vienna University of Economics and Business Information Systems and Operations Management Vienna Austria Center for Cyber-Physical Systems Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350304602

The Internet of Vehicles (IoV), a network that interlinks vehicles, infrastructure, and assorted entities, serves as a cornerstone for intelligent transportation systems and the emergence of smart cities. Within this context, edge computing has been identified as a critical solution for providing rapid and reliable data processing. Machine Learning (ML) techniques have become essential to IoV activities such as resource allocation and load balancing across mobile edge servers, typified by decentralized services that range from natural language processing to image recognition. The fusion of ML with edge computing within IoV architecture promises enhanced performance, efficiency, and safety. However, this amalgamation also creates challenges related to data privacy, cybersecurity, malfunctioning edge devices, inconsistent network connectivity, human errors, and malicious insiders. Consequently, this paper focuses on modeling security threats within an ML-based edge computing framework for the IoV. We analyze the system provided by the Linux Foundation Edge Akraino Project's Stable Topology Prediction blueprint by employing a hybrid threat modeling technique. Our strategy leverages STRIDE to elicit threats on distinct system elements like vehicle-to-vehicle communication networks, edge networks, and ML models. Subsequently, these threats are consolidated for a comprehensive view using an attack tree. © 2023 ieee.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Efficiency Redefined: Impact of Reducing data acquisition Rate for Optimized TinyML in Resource-Constrained IoT Devices 17

Efficiency Redefined: Impact of Reducing Data Acquisition Ra...

引用

17th international conference on COMmunication systems and NETworkS, COMSNETS 2025

作者： Saha, Bidyut Samanta, Riya Ghosh, Soumya K. Roy, Ram Babu Indian Institute of Technology Kharagpur India

ISBN: (纸本)9798331531195

Tiny Machine Learning (TinyML) enables cost-effective, privacy-focused machine learning inference on micro-controller units (MCUs) connected to sensors. For these resource-limited settings, achieving an optimized design is essential. This study examines the impact of reducing data acquisition rates on TinyML models designed for time series classification, especially in battery-powered IoT devices with tight resource constraints. By decreasing sampling frequency, we aim to lower computational requirements - such as RAM usage, energy consumption, latency, and multiply-accumulate (MAC) operations - by approximately four times while preserving classification accuracy. Experiments conducted with six benchmark datasets (UCIHAR, WISDM, PAMAP2, MHEALTH, MIT-BIH, and PTB) indicate that reduced data acquisition rates substantially lessen energy demands and computational overhead with minimal impact on accuracy. For instance, lowering the acquisition rate by 75% for the MIT-BIH and PTB datasets resulted in a 60% reduction in RAM use, 75% fewer MAC operations, 74% shorter latency, and a 70% decrease in energy consumption, all without compromising accuracy. These findings offer key insights into the deployment of optimized TinyML models in constrained environments. © 2025 ieee.

关键词： Machine Learning Neural Network Optimization On-Device computing Resource-constrained Environments TinyML

来源：评论

学校读者我要写书评

暂无评论

Explaining Cyber Risks in Transportaion 5.0: A data Driven Approach 4

Explaining Cyber Risks in Transportaion 5.0: A Data Driven A...

引用

4th ieee international conference on Artificial Intelligence in Cybersecurity, ICAIC 2025

作者： Tandan, Binod Vajpayee, Prashant Hossain, Gahangir University of North Texas Dept. of Informtation Science DentonTX United States

ISBN: (纸本)9798331518882

The primary objective of the research is to explore the cybersecurity risks associated with AI-enabled intelligent transportation systems (Transportation 5.0) within the context of developing future smart cities. In Transpiration 5.0, the critical infrastructure increasingly relies on automated systems, which enhances the threat of ransomware attacks, specifically targeting vital cyber-physical systems (CPS), smart grids, and intelligent transportation systems (ITS). The paper explores transportation ransomware attack data to incorporate advanced visualization and extract relevant data attributes for cyber risk evaluation. The study uses the NIST risk management framework and ISACA risk quantification to develop a cyber risk evaluation method. With the findings of the literature review, the research highlights ransomware as a significant threat to intelligent transportation systems (ITS), given the negative impact of malware on IoT, IIoT, and network-connected devices. While substantial research exists on malware detection techniques, performance, accuracy, and cloud-based strategies, it's crucial for organizations to comprehend the risks of ransomware attacks to implement effective security controls and enable cyber excellence. The research executes exploratory data analysis on the given dataset to find out the correlation between different attributes such as severity, data loss, affected systems, and ransom amount for evolving a risk method to evaluate cyber risk. The focus is to simplify the risk evaluation process by fitting the right data attributes into a standard risk management framework and risk formula for broader reusability. The method was applied to different transportation modes to calculate the risk scores respectively and generate insights accordingly. The overall analysis supports that effective risk predictions along with consistent monitoring can help to control ransomware attack incidents and improve cyber resiliency. This paper proposes a data-d

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

Improvment of Measurement systems for Relative Quality Indicator by Immitance Parameters 11

Improvment of Measurement Systems for Relative Quality Indic...

引用

11th ieee international conference on intelligent data acquisition and advanced computing systems - Technology and Applications (IDAACS)

作者： Yatsuk, Vasyl Bubela, Tetiana Pokhodylo, Yevhen Zdeb, Volodymyr Lviv Polytech Natl Univ 28a Bandery Str UA-79013 Lvov Ukraine

ISBN: (纸本)9781665426053

The structure of the measuring system for precise determination of the relative quality indicator of non-conductive objects is improved. This indicator is determined relative to the parameters of the code controlled measures. To increase the accuracy of the value of the relative quality index, which is determined by the separation of the two results of the transformation, which is proportional to the control and sample components of the admittance. These components are obtained with a time division of channels. The metrological properties of the proposed structure will be practically determined only by the parameters of the code-controlled measure.

关键词： relative indicator quality differential method of measurement RLC-parameters code-controlled measures means

来源：评论

学校读者我要写书评

暂无评论

data Fusion of Semantic and Depth Information in the Context of Object Detection 2

Data Fusion of Semantic and Depth Information in the Context...

引用

2nd international conference on intelligent Cyber Physical systems and Internet of Things (ICoICI)

作者： Abu Yusuf, Md Khan, Md Rezaul Karim Saha, Partha Pratim Rahaman, Mohammed Mahbubur Tech Univ Chemnitz Fac Comp Sci Chemnitz Germany Maharishi Int Univ Dept Comp Sci Fairfield IA USA

ISBN: (纸本)9798331540661;9798331540678

Considerable study has already been conducted regarding autonomous driving in modern era. An autonomous driving system must be extremely good at detecting objects surrounding the car to ensure safety. In this paper, classification, and estimation of an object's (pedestrian) position (concerning an ego 3D coordinate system) are studied and the distance between the ego vehicle and the object in the context of autonomous driving is measured. To classify the object, faster Region-based Convolution Neural Network (R-CNN) with inception v2 is utilized. First, a network is trained with customized dataset to estimate the reference position of objects as well as the distance from the vehicle. From camera calibration to computing the distance, cutting-edge technologies of computer vision algorithms in a series of processes are applied to generate a 3D reference point of the region of interest. The foremost step in this process is generating a disparity map using the concept of stereo vision.

关键词： Autonomous driving Computer vision Faster RCNN Object detection Stereo vision

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 << < 100 101 102 103 104 105 106 107 108 109 > >>

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：