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

20,374 篇 会议
162 篇 期刊文献
80 册 图书
1 篇 学位论文

馆藏范围

20,617 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

12,851 篇 工学
- 8,376 篇 计算机科学与技术...
- 5,060 篇 软件工程
- 5,049 篇 信息与通信工程
- 4,651 篇 电气工程
- 1,503 篇 控制科学与工程
- 1,332 篇 电子科学与技术（可...
- 1,232 篇 光学工程
- 908 篇 生物医学工程（可授...
- 884 篇 机械工程
- 841 篇 仪器科学与技术
- 813 篇 生物工程
- 347 篇 网络空间安全
- 297 篇 交通运输工程
- 293 篇 化学工程与技术
- 291 篇 安全科学与工程
- 261 篇 动力工程及工程热...
- 192 篇 建筑学
- 183 篇 土木工程
4,697 篇 理学
- 2,163 篇 数学
- 2,082 篇 物理学
- 880 篇 生物学
- 673 篇 统计学（可授理学、...
- 522 篇 系统科学
- 349 篇 化学
1,544 篇 医学
- 1,409 篇 临床医学
- 383 篇 基础医学(可授医学...
- 269 篇 药学(可授医学、理...
1,409 篇 管理学
- 848 篇 管理科学与工程(可...
- 632 篇 图书情报与档案管...
- 213 篇 工商管理
211 篇 法学
139 篇 农学
81 篇 经济学
69 篇 军事学
64 篇 教育学
45 篇 文学
24 篇 艺术学
1 篇 哲学
1 篇 历史学

主题

1,121 篇 image segmentati...
1,072 篇 signal processin...
1,068 篇 image coding
1,016 篇 image processing
1,000 篇 internet of thin...
957 篇 feature extracti...
831 篇 image reconstruc...
634 篇 internet
561 篇 signal processin...
496 篇 signal to noise ...
489 篇 deep learning
476 篇 image edge detec...
459 篇 training
426 篇 image color anal...
405 篇 image enhancemen...
402 篇 cameras
401 篇 robustness
306 篇 image resolution
298 篇 accuracy
293 篇 image recognitio...

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...
24 篇 university of el...
24 篇 center for signa...
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
26 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 wang wei
17 篇 zhang yan
16 篇 wang lei
16 篇 takahiro ogawa
16 篇 ghassan alregib

语言

18,742 篇 英文
1,789 篇 其他
78 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 20617 条记录，以下是1101-1110 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：

UAV image Denoising based on Swin Deformer for Power System Condition Monitoring 8

UAV Image Denoising based on Swin Deformer for Power System ...

引用

8th international conference on Intelligent Computing and signal Processing, ICSP 2023

作者： Wang, Dong Ye, Linwei Xi'an Jiaotong-Liverpool University Department of Mechanics and Robotics Systems Suzhou China Xi'an Jiaotong-Liverpool University Department of Information Management and Information System Suzhou China

ISBN: (纸本)9798350302455

In order to improve the quality of UAV transmission line inspection pictures and ensure the effectiveness of the defect recognition network, this paper proposes a model based on Swin Deformer to denoise the pictures. The data set of this method is the original data set collected by UAV, and the test set and training set are obtained by classifying the raw data. At the same time, Gaussian noise is added to generate tags to ensure the effect of supervised learning. Finally, the test set is input into the pre-training model, and the results obtained prove that our noise reduction network can greatly improve the image quality and further improve the effect of line maintenance. © 2023 ieee.

关键词： image enhancement

来源：评论

学校读者我要写书评

暂无评论

GNSS deformation monitoring analysis based on the spatio-temporal Kalman filter: A comparison study 6

GNSS deformation monitoring analysis based on the spatio-tem...

引用

6th international conference on Intelligent Control, Measurement and signal Processing, ICMSP 2024

作者： Chen, Yajie Mu, Kai Tan, Jia Wang, Chao Chen, Lin Xiong, Jun State Grid Corp. of China Qingpu Power Supply Co. Shanghai China Shanghai Huace Navigation Technology Ltd. Shanghai China Nanjing University of Posts and Telecommunications School of Internet-of-Things Nanjing China

ISBN: (纸本)9798331516550

Kalman filter (KF) is a widely applied technique for deformation monitoring, which can estimate the deformation displacement from the noisy Global navigation satellite system (GNSS) measurements. This work compares the traditional KF and spatio-temporal Kalman filter (STKF) from the aspect of algorithm models and simulation results. The algorithm implementation of KF and STKF for deformation monitoring are given and analyzed in detail. In the case of stable deformation process, results show that both methods can accurately estimate the deformation displacement. In the case of sudden deformation process, such as burst step displacement and slope displacement, STKF outperforms KF via its spatio-temporal modelling. based on the Kriging model, STKF can fully exploit the correlation among different monitoring points, then estimate the deformation without low delay. © 2024 ieee.

关键词： Kalman filters

来源：评论

学校读者我要写书评

暂无评论

16th international conference on Wireless Communications and signal Processing, WCSP 2024

16th International Conference on Wireless Communications and...

引用

16th international conference on Wireless Communications and signal Processing, WCSP 2024

ISBN: (纸本)9798350390643

The proceedings contain 253 papers. The topics discussed include: near-field attitude and location estimation based on partitioned large-scale antenna array;CKM-based environment-aware pilot reuse and channel estimation;analysis of sliding-correlation frame synchronization for visible light communication with signal-dependent noise;optimizing age of information for multi-antenna aided covert communications;PLMS: a packet loss memory-based transmission enhancement scheme for GEO satellite networks;interference management for IRS-NOMA networks via constructive interference;impacts of blockages on UAV-enabled integrated sensing and communications;robust image watermarking based on texture guidance and dynamic multi-spectrum attention;refined parity-check polar codes from PAC codes with lower complexity;and resource allocation in a dual-sensor update system for age of information minimization.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Intelligent Automation System for Energy Conservation Using IoT and Machine Learning 7

Intelligent Automation System for Energy Conservation Using ...

引用

7th international conference on Electronics, Communication and Aerospace technology, ICECA 2023

作者： Kumar, B.Sakthi Ramalingam, S. Viveka, S. Vigneshwar, V.G. Sivasubramaniam, N. Maria, J.Sancta Sri Eshwar College of Engineering Department of ECE Coimbatore India

ISBN: (纸本)9798350340600

People's busy and comfortable lifestyles in our technological era have enabled communication technology to advance to the point where any information may be accessed from anywhere in the world. Technological revolutions such as the internet of Things and machine learning have grown in popularity in recent years due to the benefits they represent in a variety of domains of expertise. It is worth noting that implementing these two technologies encourages the development of more and better-automated systems of control in the home automation area that adapt to the preferences of each user. Many instances occur at establishments as a result of negligence and forgetfulness, when electrical equipment is left on even when there is no human presence in the room. This is one of the most prominent examples of societal electrical waste. As a result, a smart system that ensures both efficacy and efficiency must be implemented. To solve this issue, a privacy-preserving and safe identification and verification methodology for Home Automation systems that leverages strong current technologies such as IoT, Machine Learning (ML), and image Processing are proposed. It additionally makes utilization of more efficient image processing technologies than IR sensor-based systems for home automation. The ML Algorithm is responsible for recognizing people in each frame captured by the camera. A robust machine learning system capable of accurately distinguishing diverse environmental variables and human activities is designed to manage challenging situations. © 2023 ieee.

关键词： internet of things

来源：评论

学校读者我要写书评

暂无评论

ECG Anomaly Detection with LSTM-Autoencoder for Heartbeat Analysis

ECG Anomaly Detection with LSTM-Autoencoder for Heartbeat An...

引用

2024 ieee international conference on Consumer Electronics, ICCE 2024

作者： Farady, Isack Patel, Vraj Kuo, Chia-Chen Lin, Chih-Yang National Central University Taiwan Marwadi University India National Center for High-performance Computing Taiwan

ISBN: (纸本)9798350324136

Electrocardiogram (ECG) signals are central to cardiac health assessment but interpreting them accurately requires expertise. Traditional methods often lack interpretability, posing limitations in ECG signal analysis. In this study, we propose an LSTM-based autoencoder to detect anomalies in 1D ECG signals, taking inspiration from 2D image anomaly detection techniques. Our model addresses the limitations of conventional methods and enhances ECG signal analysis accuracy. Due to the scarcity of annotated ECG datasets, we adopt an unsupervised anomaly detection approach by harnessing LSTM-based autoencoders. This enables us to uncover underlying patterns in ECG signals, facilitating the detection of abnormal patterns without the need for explicit labeling. Experimental results demonstrate that our LSTM-based autoencoder produces competitive outcomes. This work underscores the potential of deep learning approaches to enhance both the accuracy and efficiency of anomaly hearbeat in ECG signals. © 2024 ieee.

关键词： autoencoder model deep learning electrocardiogram signal long short-Term memory time-series anomaly detection

来源：评论

学校读者我要写书评

暂无评论

An Approach based on Multi-Entropy and Artificial Intelligence for Communication Modulation signal Identification

An Approach Based on Multi-Entropy and Artificial Intelligen...

引用

2023 ieee international conference on image Processing and Computer Applications, ICIPCA 2023

作者： Guo, Ziyuan Miao, Le Lin, Yifan School of Electronic and Information Engineering Beijing Jiaotong University Beijing China School of Communication and Information Engineering Xi'an University of Posts and Telecommunications Xi'an China

ISBN: (纸本)9798350314670

With the increasingly complex electromagnetic influence in the modern communication environment and the explosive growth of communication business data, the modulation recognition system needs to constantly learn new modulation categories and signal characteristics in the process of data increment, and gradually acquire stronger modulation recognition capability. This paper proposes a communication modulation signal recognition method based on multi-entropy and artificial intelligence technology. Firstly, the power entropy, singular spectral entropy, sample entropy, fuzzy entropy, and permutation entropy of the signal are calculated, and a composite entropy feature calculation method based on entropy weight method is proposed to further study the feature extraction of the signal. Finally, it is found that when using neural network for learning, without feature extraction, the recognition accuracy rate is only 70.7%, while using the feature extraction method proposed in this paper, the accuracy rate can reach 89.5%, and the recognition speed is significantly improved. In addition, the feature extraction method proposed in this paper can improve all kinds of modulation recognition based on artificial intelligence. © 2023 ieee.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Reinforcement Learning for Adaptive Traffic signal Control Using Deep Q-Networks 1

Reinforcement Learning for Adaptive Traffic Signal Control U...

引用

1st international conference on Sustainable Energy Technologies and Computational Intelligence, SETCOM 2025

作者： Bohra, Asha Rani Selvi, Thamarai Vishal, V. Sunkara, Pawan Sai Sunku, Balaji Jignesh, Bhavsar Nitya New Horizon College of Engineering Dept. of Computer Science and Engineering Karnataka Bengaluru India New Horizon College of Engineering Dept. of Information Science and Engineering Karnataka Bengaluru India

ISBN: (纸本)9798331520540

Traffic congestion is a critical issue in urban areas, contributing to increased travel time, fuel consumption, and environmental pollution. Traditional traffic signal control methods, such as fixed-time systems, cannot adapt to real-time changes in traffic conditions. This paper presents a novel approach using Deep Q-Networks (DQN) to control traffic signals based on realtime traffic data dynamically. Our simulation environment models a four-way intersection, where vehicle densities and wait times are continuously monitored. The DQN agent optimizes green light durations by minimizing vehicle wait times and maximizing traffic throughput. Extensive simulation results demonstrate that our system significantly reduces congestion and improves traffic flow compared to traditional fixed-time systems. Furthermore, the approach shows potential for real-world applications in urban traffic control systems, particularly in smart cities equipped with internet of Things (IoT) devices. © 2025 ieee.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Channel Adaptive Decoding in Underwater Optical Camera Communication systems 5

Channel Adaptive Decoding in Underwater Optical Camera Commu...

引用

5th international conference on Advanced Research in Computing, ICARC 2025

作者： Aberathna, Thimuthu Kumarage, Miyuni Atthanayake, Nuwan Sri Lanka Technology Campus Faculty of Engineering Padukka Sri Lanka

ISBN: (纸本)9798331530983

Underwater optical camera communication (UOCC) systems that use light-emitting diodes as transmitters and high-frame rate cameras as receivers offer robust and low-cost wireless communication solutions for underwater applications compared to traditional methods. However, its performance is greatly affected by the varying underwater environments such as turbulence, salinity, and oceanic currents. This is mainly due to fixed image processing and data decoding algorithms used in UOCC systems don't provide adaptive methods that change with the underwater environments. To this end, we introduce an adaptive threshold-based algorithm to enhance the system's performance by dynamically adjusting the threshold values used in the decoding algorithm on real-time channel *** this context, adaptive thresholding refers to selecting optimal threshold values for various transmission scenarios, ensuring robust data decoding tailored to specific environmental challenges. This paper presents a comprehensive analysis of the presented algorithm under four distinct channel conditions, such as clear water, muddy water, air bubbles, and chlorophyll water. Our simulations and experiments demonstrate the effectiveness of the adaptive threshold-based algorithm in improving bit error rate (BER), making UOCC more reliable and robust in diverse underwater conditions for short-range applications. The BER performance of the presented algorithm in clear water is nearly zero, while under the other three conditions, it is approximately 1 × 10-3 within a 1-meter communication distance. © 2025 ieee.

关键词： signal systems

来源：评论

学校读者我要写书评

暂无评论

image Compression Algorithm based on Region of Interest Extraction for Unmanned Aerial Vehicles Communication 8

Image Compression Algorithm Based on Region of Interest Extr...

引用

8th ieee Information technology and Mechatronics Engineering conference, ITOEC 2025

作者： Liang, Yanxia Jia, Tong Liu, Xin Zhang, Huanhuan Xi'an University of Posts and Telecommunications Shaanxi Key Laboratory of Information Communication Network and Security Xi'an China Xi'an Eurasia University College of Information Engineering Xi'an China

ISBN: (纸本)9798331517915

The flexibility and maneuverability of unmanned aerial vehicles (UAVs) have led to their widespread use, but the challenge of limited storage space and bandwidth in emergency scenarios necessitates efficient image compression techniques. In this research, we propose an image compression algorithm tailored for UAV communication, termed ROIE-UC (Region of Interest Extraction for UAV Communication). Firstly, image pixels are clustered into super pixel blocks using the Simple Linear Iterative Clustering (SLIC). Secondly, these super pixels are grouped into regions of interest (ROI) using the Density-based Spatial Clustering of Applications with Noise (DBSCAN). The image is then segmented into ROI and non-ROI areas based on these clusters. Lossless compression is applied to the ROI, while lossy compression with a high ratio is used for non-ROI regions. At the receiving end, the image is decompressed and reconstructed. Experimental results show that the ROIE-UC achieves a Peak signal-to-Noise Ratio (PSNR) of 46.37 dB and a Structural Similarity Index (SSIM) of 99.94% for the ROI part, with compression ratios of 27, 25, and 14 for the whole image. Compared to the JPEG, PSNR improved by up to 28.52% and SSIM by 1.51%, with a compression ratio increase from 14.52 to 27.56. The ROIE-UC also provides up to a 49.44% increase in PSNR over other methods. These results demonstrate that ROIE-UC is an efficient and effective solution for image processing and data compression in UAV applications. © 2025 ieee.

关键词： image compression

来源：评论

学校读者我要写书评

暂无评论

IOT based Virtual Telepresence Robot 3

IOT Based Virtual Telepresence Robot

引用

3rd ieee international conference on Intelligent Techniques in Control, Optimization and signal Processing, INCOS 2024

作者： Pon Pushpa, S. Ewins Jayasree, T. Mariammal, K. Selwyn, Chris Jonathan Solomon, S. Benny Raj, S. Harish College of Engineering Anna University Department of Ece Guindy Chennai India Madras Institute of Technology Anna University Department of Electronics Engg. Chrompet Chennai India

ISBN: (纸本)9798350361186

This paper, marks an innovative exploration of robotics, IoT, and telepresence technologies, aiming to create a versatile and user-friendly robot, for remote control and real-time presence in distant locations. The key components and functionalities of this work, include the ESP32 micro controller, which serves as the central brain, interfacing with an analog joystick for user control. The Raspberry Pi camera, integrated through Message Queuing Telemetry Protocol, enhances capabilities, with high-quality real-time video, streaming to provide an immersive experience. The L298N motor driver facilitates precise control over the robot's mobility, allowing it to navigate in any direction. ESP32's role in interfacing with the analog joystick, for movement control is emphasized. As a conclusion, the integration of hardware and software components, in the development of the IoT based Virtual telepresence robot, represents a significant leap forward in the realm of remote robotics. © 2024 ieee.

关键词： internet of things

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 << < 107 108 109 110 111 112 113 114 115 116 > >>

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：