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

2,918 篇 会议
19 篇 期刊文献
14 册 图书

馆藏范围

2,951 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,958 篇 工学
- 1,321 篇 计算机科学与技术...
- 946 篇 软件工程
- 815 篇 信息与通信工程
- 549 篇 电气工程
- 286 篇 控制科学与工程
- 261 篇 电子科学与技术（可...
- 190 篇 仪器科学与技术
- 172 篇 生物医学工程（可授...
- 160 篇 机械工程
- 160 篇 生物工程
- 110 篇 网络空间安全
- 96 篇 光学工程
- 91 篇 动力工程及工程热...
- 77 篇 材料科学与工程（可...
- 75 篇 化学工程与技术
- 70 篇 石油与天然气工程
- 58 篇 交通运输工程
- 51 篇 安全科学与工程
862 篇 理学
- 458 篇 数学
- 261 篇 物理学
- 184 篇 生物学
- 139 篇 化学
- 138 篇 统计学（可授理学、...
- 66 篇 系统科学
397 篇 管理学
- 236 篇 管理科学与工程(可...
- 196 篇 图书情报与档案管...
- 81 篇 工商管理
222 篇 医学
- 197 篇 临床医学
- 115 篇 基础医学(可授医学...
- 81 篇 药学(可授医学、理...
38 篇 法学
30 篇 经济学
23 篇 农学
18 篇 教育学
14 篇 军事学
3 篇 文学

主题

221 篇 signal processin...
117 篇 signal processin...
101 篇 data mining
76 篇 feature extracti...
68 篇 big data
67 篇 digital signal p...
57 篇 data acquisition
54 篇 signal to noise ...
50 篇 machine learning
48 篇 deep learning
46 篇 data models
40 篇 support vector m...
34 篇 training
32 篇 electroencephalo...
31 篇 data processing
31 篇 real-time system...
30 篇 array signal pro...
28 篇 image processing
28 篇 accuracy
26 篇 neural networks

机构

49 篇 maharishi school...
37 篇 centre of interd...
16 篇 department of ar...
15 篇 vishwakarma inst...
12 篇 department of el...
12 篇 department of co...
11 篇 department of sc...
11 篇 vivekananda glob...
9 篇 department of co...
8 篇 department of el...
8 篇 chitkara univers...
8 篇 prince shri venk...
8 篇 prince shri venk...
8 篇 key laboratory o...
8 篇 vivekananda glob...
8 篇 department of el...
7 篇 school of comput...
7 篇 key laboratory o...
7 篇 american interna...
7 篇 insight sfi rese...

作者

7 篇 md. rifat hazari
7 篇 hamdulla askar
7 篇 chakravarthi bha...
6 篇 kumaresan prasan...
6 篇 ablimit mijit
6 篇 ahmad tohari
6 篇 gao yanxia
6 篇 liu yiwen
5 篇 abir ahmed
5 篇 vikrant bhateja
5 篇 suresh chandra s...
5 篇 wang wei
5 篇 bekkay hajji
5 篇 chang chin-chen
5 篇 ramakrishnan ram...
5 篇 md. saniat rahma...
5 篇 zhang ying
4 篇 li li
4 篇 priyadharshini r...
4 篇 liu xin

语言

2,864 篇 英文
80 篇 其他
15 篇 中文
1 篇 俄文

检索条件"任意字段=3rd International Conference on Signal and Data Processing, ICSDP 2023"

共 2951 条记录，以下是31-40 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：

data Acquisition and Pre-processing of EEG signals Using Brainwave Sensor

Data Acquisition and Pre-processing of EEG Signals Using Bra...

引用

3rd international conference on signal and data processing, icsdp 2023

作者： Negi, Anju Apeksha, S. Bharath, C.H. Uzair, Mohamed PES University 100 ft Ring Road Banashankari Stage III Dwaraka Nagar Banashankari Karnataka Bengaluru560085 India

ISBN: (纸本)9789819795772

Many brain disorders are very critical and need to be detected at an early stage. This demands the need to create a reliable low-cost, portable system that can acquire the signals and then process and analyze that data. Through this project, the authors aim to address this problem by creating a pre-processing system for an EEG data acquisition system which acquires EEG signals then processes the data to remove noise, and analyze the signal to provide valuable insights. The device is built with several high-pass, low-pass, and notch filters to condition the signal and instrumentation amplifiers for further amplification. An overall amplification of 90× in the first stage and 450× in the last stage is achieved. With the hardware in place, work has been done to integrate the data acquisition system with RLS adaptive filtering algorithms to further enhance the EEG signals by removing EOG artifacts. Later, the signal is analyzed using wavelet transformation and separated into different band frequencies. The proposed post processing system is set to analyze the acquired data for critical brain disorders like depression detection and autism severity indication by using novel approaches. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wavelet decomposition

来源：评论

学校读者我要写书评

暂无评论

A Spatio-Temporal Multi-Subgraph Convolutional Network for Parkinson’s Disease Detection Using Gait data 24

A Spatio-Temporal Multi-Subgraph Convolutional Network for P...

引用

3rd international conference on Artificial Intelligence and Intelligent Information processing, AIIIP 2024

作者： Wu, Huimin Liu, Yongcan Wang, Xianquan Yu, Xinglin Zhao, Aite College of Computer Science and Technology Qingdao University Shandong Qingdao China Institute of Advanced Technology University of Science and Technology of China Anhui Hefei China

ISBN: (纸本)9798400707308

Gait disturbance is a key motor symptom of Parkinson’s disease (PD) and has been widely studied for diagnosis and severity assessment using non-invasive sensor data. However, most existing methods for PD detection struggle to adaptively model sensor positions and inter-signal correlations within a multi-sensor system. Additionally, these sensors form a complex system with multiple subsystems monitoring local regions, and their interrelations are often overlooked. In this work, we propose a spatio-temporal multi-subgraph convolutional network (ST-MSGCN), a hybrid framework using graph neural networks to capture gait differences between healthy individuals and PD patients from multi-sensor data. We first decouple the overall sensor system and encode inter-subsystem correlations into multiple subgraphs. The ST-MSGCN then employs a spatio-temporal graph convolutional network to analyze 3D-graph representations of foot force signals, exploring spatial and temporal characteristics within each subgraph. We also introduce channel-wise topology and temporal attention mechanisms into the graph convolutional layers to dynamically learn discriminative features. Finally, a decision-making layer using a voting strategy fuses observations and state estimations from multiple graphs. The proposed method is validated on the PDgait dataset and compared with several existing models. Additionally, it is evaluated on a normal skeleton-based dataset to explore the relationships among body parts. © 2024 Copyright held by the owner/author(s).

关键词： Neurodegenerative diseases

来源：评论

学校读者我要写书评

暂无评论

Joint Optimization of Computation Offloading, Dynamic Pricing and Admission Control in Mobile Edge Computing-Enable Blockchain 24

Joint Optimization of Computation Offloading, Dynamic Pricin...

引用

3rd international conference on signal processing, Computer Networks and Communications, SPCNC 2024

作者： Liu, Yi Zhang, Wenjie Zheng, Yifeng Chen, Liming Key Lab of Data Science and Intelligence Application School of Computer Sciences Minnan Normal University Fujian Zhangzhou China Zhangzhou Affiliated Hospital of Fujian Medical University Fujian Zhangzhou China

ISBN: (纸本)9798400710834

In order to cope with the problem of insufficient resources on mobile devices, the combination of blockchain and Mobile Edge Computing (MEC) has attracted much attention. In this paper, we consider an edge-enabled blockchain system containing two types of miners and a single Edge Service Provider (ESP). Different types of miners have different resource requirements and corresponding prices. Each miner makes a computation offloading decision based on the resource price set by ESP. Different miners possess varying resource requirements and correspond to distinct prices. Miners formulate task offloading decisions based on the prices set by ESP for different resource types. The ESP dynamically adjusts resource price based on miners’ offloading requests and makes admission control according to resource usage in each time slot. The problem is a joint optimization problem of computation offloading, price strategy, and admission control, we model the problem as a sequential decision-making problem and use a dynamic programming algorithm to obtain the optimal solution. Through simulation experiments, our results demonstrate that the proposed algorithm can effectively improve the overall social utility. © 2024 Copyright held by the owner/author(s).

关键词： Computation offloading

来源：评论

学校读者我要写书评

暂无评论

Deep Learning for Automated Image Captioning: A CNN and Transformer Model Analysis 3

Deep Learning for Automated Image Captioning: A CNN and Tran...

引用

3rd international conference on Intelligent data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Saarika, Kathula Varsha, Vasaraju Sri Harsha, P. Sheikh, Anjum Nabi Dept. Artificial Intelligence and Data Science Chaitanya Bharathi Institute of Technology India

ISBN: (纸本)9798331527549

Automatic image captioning is a multidisciplinary effort that combines machine learning, natural language processing, and computer vision in creating meaningful and context-rich captions for images. Within a short time, this research problem has garnered a lot of attention and new techniques are continuously being proposed. However, there are many dismaying factors as well. For instance, the current models still have a long way to go in attaining human accuracy. This paper seeks to conduct a systematic review of the recent trends and developments in the field of image captioning techniques and models with a focus on 2023 and 2024 by systematically analyzing the 13 publications located in Springer and IEEEXplore libraries. According to our research, Convolutional Neural Networks allow the identification of image content at an early stage, and Recurrent Neural Networks or Long Short-Term Memory networks usually appear at the text generation stage. The most common image datasets are MS COCO and Flickr8k. Almost all studies utilized the BLEU scores (1, 2, 3, and 4) mechanism. It is alleviated that CNN with LSTM models tends to perform better when compared to RNN-modeled networks. Attention mechanisms and Encoder-Decoder architecture are aggressively becoming the two major solutions to strengthening image captioning. This review will help and provide direction to those who are interested in practicing research that aims to promote the techniques and processes of automatic image captioning. © 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

Object-level data Augmentation for Visual 3D Object Detection in Autonomous Driving

Object-level Data Augmentation for Visual 3D Object Detectio...

引用

2025 IEEE international conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Cheng, Haoran Xu, Junkai Peng, Liang Yang, Zheng He, Xiaofei Wu, Boxi Zhejiang University Hangzhou310027 China FABU Inc. Hangzhou310030 China

ISBN: (纸本)9798350368741

data augmentation plays an important role in visual-based 3D object detection. Existing detectors typically employ image/BEV-level data augmentation techniques, failing to utilize flexible object-level augmentations because of 2D-3D inconsistencies. This limitation hinders us from increasing the diversity of training data. To alleviate this issue, we propose an object-level data augmentation approach that incorporates scene reconstruction and neural scene rendering. Specifically, we reconstruct the scene and objects by extracting image features from sequences and aligning them with associated LiDAR point clouds. This approach is intended to conduct the editing process within a 3D space, allowing for flexible object manipulation. Additionally, we introduce a neural scene renderer to project the edited 3D scene onto a specified camera plane and render it onto a 2D image. Combined with scene reconstruction, it overcomes the challenges stemming from 2D/3D inconsistencies, enabling the generation of object-level augmented images with corresponding labels for model training. To validate the proposed method, we apply our method to various multi-camera 3D object detectors, consistently boosting the performance. © 2025 IEEE.

关键词： data augmentation Visual 3D object detection

来源：评论

学校读者我要写书评

暂无评论

Comparative Analysis of Neural Network Models for Error Probability Prediction in Vehicular Communication 3rd

Comparative Analysis of Neural Network Models for Error Prob...

引用

3rd international conference on Computational Electronics for Wireless Communications, ICCWC 2023

作者： Reshma, P. Gautam, Jatin Sudha, V. National Institute of Technology Tiruchirappalli Tamil Nadu Tiruchirappalli India

ISBN: (纸本)9789819719426

Reliable data transfer is a tedious task for various applications that involve users in motion. In vehicular communication systems, for reliable and seamless data transfer an accurate estimation strategy is needed. The principal objective involves construction of the predictive models that can estimate error probabilities on parameters like signal strengths, timestamps, and sender identification outcomes. To establish a proper strategy for vehicle scenarios while maintaining the system’s effectiveness, we present an analysis of our system with error probabilities, exploring the relationship between signal strength, neural network (NN) architectures, and error prediction accuracy. data generated is used to simulate communication messages. Furthermore, this paper boards to calculate the effectiveness of different NN architectures, including single and multi-layer perceptrons, interpreting key relations embedded in data and providing precise error probability predictions. Through a series of insights, we observed signal strength and NN impact on error predictions. Our analysis improves the complex error pattern occurrences and identifies the most suitable architecture for accurate predictions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Accuracy Error prediction Neural networks Reliable data transfer signal strength

来源：评论

学校读者我要写书评

暂无评论

Research on the Application of Cloud Computing-based Dual-Machine Hot Standby System in Railway signal Safety Management 3

Research on the Application of Cloud Computing-based Dual-Ma...

引用

3rd international conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Ji, Zhe Wang, Ding Liu, Bing Liu, Yiming Research and Design Institute Co. Ltd Shenzhen China China Academy of Railway Sciences Co. Ltd Beijing China

ISBN: (纸本)9798331508456

This paper investigates the application of cloud computing-based dual-computer hot standby computer security platform in railway signalling security management, aiming to enhance the reliability and security of railway signalling system. With the increasing importance of railway transport to modern society, the safety of railway signal system has become a key factor for public safety and social stability. This paper first analyses the security challenges faced by railway signalling systems and explores the potential of dual-machine hot-standby systems in improving system availability and security. Then, this paper details the design and implementation of a cloud-based dual-machine hot standby architecture, including system architecture, signal monitoring module, data encryption module, security audit module, and event response module. Through experimental validation, this paper compares the performance of the cloud-based dual-machine hot-standby architecture with that of the traditional single-machine system in terms of failure recovery time, resource utilisation and system response time, and the results show that the dual-machine hot-standby architecture has significant advantages in these key performance indicators. Finally, the paper discusses the limitations of the research and proposes directions for future research, including cost-benefit analysis, resource optimisation, technology adaptation research and intelligent development, with a view to providing a more efficient and intelligent solution for railway signal safety management. © 2025 IEEE.

关键词： Subway signal systems

来源：评论

学校读者我要写书评

暂无评论

High-Speed Area Efficient Approximate Kogge–Stone Adder 3rd

High-Speed Area Efficient Approximate Kogge–Stone Adder

引用

3rd international conference on Computational Electronics for Wireless Communications, ICCWC 2023

作者： Dantla, Sudhakar Reddy Tummala, Prudhvi Musala, Sarada Kanapala, Satish Department of Electronics and Communication Engineering Vignan’s Foundation for Science Technology & Research Andhra Pradesh Vadlamudi India

ISBN: (纸本)9789819719426

Approximate parallel prefix adders are a type of circuit that can perform addition operations on binary numbers with high speed, low area, and less power. These circuits are designed to provide approximate results, which means that they sacrifice accuracy for efficiency. This trade-off makes them ideal for use in applications where speed is more important than precision. In recent years, there has been a growing interest in the improvement of these circuits, as they have the potential to revolutionize the field of digital signal processing. Kogge–Stone (KS) adder is a kind of parallel prefix adder that has the strong point of quickest addition primarily based on design time. Approximation Kogge–Stone (AxKS) adder is a variant of basic Kogge–Stone Adder that introduces a level of approximation in its operation. In this paper, a new approximate KS Adder is proposed with high-speed performance and less area. The KS Adder and its AxKS Adder are compared for bits 8, 16, 32 using software tool Xilinx Vivado. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Digital signal processing

来源：评论

学校读者我要写书评

暂无评论

Improved Support Vector Machine for ECG signal Classification in Implantable Biomedical Devices 3

Improved Support Vector Machine for ECG Signal Classificatio...

引用

3rd international conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Patchamatla, Pavan Srikanth SubbaRaju Balsem, Zayd Ajsan Parthiban, K.G. Ramachandra, A.C. Latha Bhuvaneswari, S. RKInfo-Tech Llc India College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Al Diwaniyah Iraq Dhaanish Ahmed Institute of Technology Department of Biomedical Engineering Coimbatore India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India Dhanalakshmi Srinivasan College Of Engineering Technology Department of Electronics and Communication Engineering Mamallapuram India

ISBN: (纸本)9798331508456

Electrocardiogram (ECG) signal classification in implantable biomedical devices plays a significant role for continuous heart monitoring and detecting cardiac abnormalities such as arrhythmias. These devices analyse ECG patterns to enable accurate diagnostics and provide necessary interventions. However, traditional ECG monitoring tools faces certain challenges like low power transfer efficiency, failure in capturing most paroxysmal Atrial Fibrillation (AFib), and difficulty in automatic determination of AFib. To solve this issue, the implantable ECG sensor with improved Support Vector Machine (SVM) is proposed to monitor the patient continuously and detect AFib effectively. The QRS complex is observed from ECG signals of 29 AFib patients is extracted by utilizing signal processing techniques such as wavelet transform and statistical analysis. The Minimum Description Length (MDL) method is applied to extract and select 12 features of variability-based heart rate parameters. Then, the improved SVM classifier with a Radial Basis Function (RBF) is used to classify the AFib in ECG data accurately. Experimental results demonstrate that the proposed implantable ECG sensor with optimized SVM achieves a better accuracy of 99.2%, sensitivity of 98.8%, specificity of 99.5%, and an F1-score of 98.9% which outperforms the existing methods like traditional SVM and CNN-based models. © 2025 IEEE.

关键词： Electrocardiograms

来源：评论

学校读者我要写书评

暂无评论

3rd international conference on Computing and Communication Networks, ICCCN 2023

3rd International Conference on Computing and Communication ...

引用

3rd international conference on Computing and Communication Networks, ICCCN 2023

ISBN: (纸本)9789819726707

The proceedings contain 60 papers. The special focus in this conference is on Computing and Communication Networks. The topics include: Enhancing Security in Wireless Sensor Networks: A Broadcast/Multicast Authentication Framework with Identity-Based Signature Schemes;TSFTO: A Two-Stage Fuzzy-Based Tasks Orchestration Algorithm for Edge and Fog Computing Environments;tracking Climatic Variations Through Smart IoT-Driven Approach: An Exploratory Analysis;Design and Manufacturing of an Efficient Low-Cost Fire Surveillance System Based on GSM Communications and IoT Technology;a Comparative Analysis of Optimized Routing Protocols for High-Performance Mobile Ad Hoc Networks;integrating Sandpiper Optimization Algorithm and Secure Aware Routing Protocol for Efficient Cluster Head Selection in Wireless Sensor Networks;the Effects of Weather Conditions on data Transmission in Free Space for Wireless Sensor Networks;Using Wireless Sensor Network Performance and Optimizing in Underground Mines with Virtual MIMO Antenna;a Novel Logistic Regression-Based Fire Detection Model Using IoT in Underground Coal Mines;An MQTT IoT Intrusion Detection System Using Deep-Learning;multi-objective Optimal Feature Selection for Cyber Security Integrated with Deep Learning;application of Gradient Boosting Classifier-Based Computational Intelligence to Detect Drug Addiction Threat in Society;insurance 4.0: Smart Insurance Technologies and Challenges Ahead;review on Vision Transformer for Satellite Image Classification;primitive Roots and Euler Totient Function-Based Progressive Visual Cryptography;approach for Fire Detection Using Image processing;review of Various Approaches for Authorship Identification in Digital Forensics;machine Learning Model for Traffic Prediction and Pattern Extraction in High-Speed Optical Networks;improved Markov Decision Process in Wireless Sensor Network for Optimal Energy Consumption.

关键词：

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296页 << < 1 2 3 4 5 6 7 8 9 10 > >>

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：