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

724 篇 会议
3 篇 期刊文献
2 册 图书

馆藏范围

729 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

474 篇 工学
- 379 篇 计算机科学与技术...
- 273 篇 软件工程
- 175 篇 信息与通信工程
- 106 篇 电气工程
- 81 篇 生物工程
- 76 篇 生物医学工程（可授...
- 47 篇 控制科学与工程
- 33 篇 电子科学与技术（可...
- 29 篇 机械工程
- 27 篇 光学工程
- 26 篇 化学工程与技术
- 18 篇 仪器科学与技术
- 14 篇 安全科学与工程
- 13 篇 交通运输工程
- 13 篇 农业工程
214 篇 理学
- 114 篇 数学
- 89 篇 生物学
- 67 篇 物理学
- 41 篇 系统科学
- 38 篇 统计学（可授理学、...
- 24 篇 化学
95 篇 医学
- 91 篇 临床医学
- 56 篇 基础医学(可授医学...
- 46 篇 药学(可授医学、理...
- 13 篇 公共卫生与预防医...
95 篇 管理学
- 57 篇 图书情报与档案管...
- 41 篇 管理科学与工程(可...
- 16 篇 工商管理
17 篇 农学
- 17 篇 作物学
11 篇 法学
- 11 篇 社会学
7 篇 教育学
6 篇 经济学
5 篇 军事学

主题

168 篇 machine learning
50 篇 deep learning
46 篇 support vector m...
46 篇 feature extracti...
41 篇 signal processin...
24 篇 signal processin...
23 篇 machine learning...
18 篇 image processing
18 篇 training
16 篇 artificial intel...
16 篇 accuracy
15 篇 electroencephalo...
14 篇 decision trees
14 篇 computer vision
13 篇 natural language...
13 篇 neural networks
13 篇 classification a...
13 篇 convolutional ne...
12 篇 data mining
12 篇 classification

机构

6 篇 xinjiang key lab...
6 篇 school of inform...
6 篇 fujian provincia...
6 篇 xinjiang key lab...
5 篇 beijing universi...
3 篇 fujian provincia...
2 篇 college of engin...
2 篇 university of jo...
2 篇 school of electr...
2 篇 china electric p...
2 篇 department of ar...
2 篇 department of it...
2 篇 valencian resear...
2 篇 ugam solutions c...
2 篇 department of co...
2 篇 chongqing univ s...
2 篇 guangzhou xinhua...
2 篇 college of elect...
2 篇 school of comput...
2 篇 guangzhou power ...

作者

10 篇 hamdulla askar
6 篇 ablimit mijit
6 篇 li zuoyong
3 篇 vysotska victori...
3 篇 teng shenghua
2 篇 veeresh
2 篇 xue jingfeng
2 篇 mohanty mihir na...
2 篇 agarwal harsh
2 篇 jin lingmin
2 篇 kalinina irina
2 篇 jia cairang
2 篇 renjith p.n.
2 篇 gozhyj aleksandr
2 篇 wen zhang
2 篇 li zheng
2 篇 selvi g. thamara...
2 篇 pandey trilok na...
2 篇 islam md. adnanu...
2 篇 kama mohd nazri

语言

700 篇 英文
28 篇 其他
4 篇 中文

检索条件"任意字段=3rd International Conference on Signal Processing and Machine Learning, SPML 2020"

共 729 条记录，以下是111-120 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：

Design of intelligent elderly care robot system based on ROS 3

Design of intelligent elderly care robot system based on ROS

引用

3rd international conference on Electronic Information Engineering and Data processing, EIEDP 2024

作者： Fan, Yu Chen, Yuanbin Chen, Chin-Ta Zhao, Jianchao Electronic and Electrical Engineering College Zhao Qing University Zhao Qing China

ISBN: (纸本)9781510680531

In order to cope with the increasing challenge of population aging worldwide, intelligent elderly care robots have become a solution that has attracted much attention. This paper constructed an intelligent elderly care Robot based on ROS (Robot Operating System), which could patrol within the specified scope, monitor the status of the elderly, potential security risks, collect physiological data of the elderly, and upload these data to the Internet of things platform in real time to share with family members or guardians. It has a comprehensive nursing function for the elderly. The design is expected to provide effective technical support and practical research for communities and social institutions, and promote the transformation and upgrading of existing pension models toward diversification and wisdom. © 2024 SPIE.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

Time-Weighted Frequency Domain Audio Representation with GMM Estimator for Anomalous Sound Detection 48

Time-Weighted Frequency Domain Audio Representation with GMM...

引用

48th IEEE international conference on Acoustics, Speech and signal processing, ICASSP 2023

作者： Guan, Jian Liu, Youde Zhu, Qiaoxi Zheng, Tieran Han, Jiqing Wang, Wenwu Harbin Engineering University Group of Intelligent Signal Processing College of Computer Science and Technology China Harbin Institute of Technology School of Computer Science and Technology China University of Technology Sydney Centre for Audio Acoustics and Vibration Australia University of Surrey Centre for Vision Speech and Signal Processing United Kingdom

ISBN: (纸本)9781728163277

Although deep learning is the mainstream method in unsupervised anomalous sound detection, Gaussian Mixture Model (GMM) with statistical audio frequency representation as input can achieve comparable results with much lower model complexity and fewer parameters. Existing statistical frequency representations, e.g. the log-Mel spectrogram's average or maximum over time, do not always work well for different machines. This paper presents Time-Weighted Frequency Domain Representation (TWFR) with the GMM method (TWFR-GMM) for anomalous sound detection. The TWFR is a generalized statistical frequency domain representation that can adapt to different machine types, using the global weighted ranking pooling over time-domain. This allows GMM estimator to recognize anomalies, even under domain-shift conditions, as visualized with a Mahalanobis distance-based metric. Experiments on DCASE 2022 Challenge Task2 dataset show that our method has better detection performance than recent deep learning methods. TWFR-GMM is the core of our submission that achieved the 3rd place in DCASE 2022 Challenge Task2. © 2023 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Detection of Parkinson's cognitive impairment patients based on motor and non-motor symptoms 3

Detection of Parkinson's cognitive impairment patients based...

引用

3rd international conference on Advanced Algorithms and signal Image processing, AASIP 2023

作者： Shi, Zhan Chen, Xi Qi, Hongbin Li, Zeyang Jiang, Hu Beijing Institute of Technology Mechanical and Electrical College Beijing100010 China

ISBN: (纸本)9781510668522

Gait measurement is an objective analysis method that can detect abnormal gait, facilitate early disease identification, and support doctors in formulating rehabilitation treatment plans. In recent years, cognitive scales and biomarkers have been widely used to detect Parkinson's cognitive impairment (PD-MCI). However, a lack of objective and reliable detection methods for PD-MCI exists. This study aims to identify patients with Parkinson's cognitive impairment utilizing two approaches: gait and executive function. Non-contact measurement was employed to obtain the gait signal, while the clock drawing test was utilized to obtain the executive function score of the patients. Ten PD-MCI patients and 10 ordinary PD were tested, and the kinematics data of the subjects during walking were recorded. Using patients' gait parameters and executive function scores as data characteristics, machine learning methods were utilized to classify and identify patients. The most suitable machine learning method for PD-MCI patient detection was discovered utilizing this approach. The results indicate that the XGBoost algorithm can identify and classify PD-MCI patients with more than 90% accuracy, providing effective support for doctors in identifying Parkinson's cognitive impairment early and customizing the most suitable rehabilitation treatment plan. These findings have significant research significance. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

32-Bit RISC Processor Using VedicMultiplier 3

32-Bit RISC Processor Using VedicMultiplier

引用

3rd international conference for Emerging Technology, INCET 2022

作者： Vishnu, Suggula Naga Sai Gandluru, Abhishek Ramesh, S.R. Coimbatore Amrita Vishwa Vidyapeetham Amrita School of Engineering Department of Electronics and Communication Engineering India

ISBN: (纸本)9781665494991

Multiplier unit is a key component in high-speed processor like Digital signal processor, graphic processor. With increase in the demand for high speed, low latency, low power and low area the demand for new techniques is high. Although several multipliers like booth multipliers, have shown some improvements in these performance parameters but Vedic multiplier based on Vedic mathematics is currently in focus due to its high speed and lower power qualities. Vedic Multiplier technique is used for fast multiplication of large numbers. It is based on"UrdhvaTriyakbhyam"which is among the 16 Vedic Sutras and which was used by ancient Indian gurusandre-discovered recently from Vedas. Multiplication serves as a key hardware block in today's technologies like machine learning, Deep learning and Digital signal processing. Previous Vedic multiplier showed promising results to use in general purpose processor. This paper presents the designof32-bitRISCprocessorusing32-bitVedicmultiplier. © 2022 IEEE.

关键词： Digital signal processing

来源：评论

学校读者我要写书评

暂无评论

Enhancing Interactive Storytelling: A Computational Approach to Autonomously Generating Role-Playing Game Scripts with Natural Language processing 3

Enhancing Interactive Storytelling: A Computational Approach...

引用

3rd international signal processing, Communications and Engineering Management conference, ISPCEM 2023

作者： Zhong, Qijun Beijing World Youth Academy Beijing China

ISBN: (纸本)9798350307023

In the realm of role-playing games (RPGs), the crafting of rich and detailed narratives is crucial, with legendary games like Dungeons & Dragons (D&D) setting the bar for creativity and player-driven storytelling. This research explores the innovative intersection of artificial intelligence and RPGs by developing a method for the automated generation of RPG scripts, harnessing the capabilities of advanced natural language processing (NLP). Our study presents an elaborate NLP framework, utilizing a comprehensive collection of D&D source materials, to methodically extract key character features (such as attributes, races, and classes) using machine learning techniques. This framework is further enhanced by integrating sentiment analysis and a sophisticated bi-directional recurrent neural network equipped with a multi-head attention mechanism. This combination is instrumental in accurately modeling narrative elements like event sequences, causal relationships, and thematic links. The culmination of this process is the automated generation of diverse and engaging RPG scripts, each characterized by distinct character dynamics, immersive settings, and compelling story arcs. The effectiveness and impact of these generated scripts were evaluated through a user study that gathered both qualitative and quantitative data. The findings demonstrate our system's proficiency in creating narratives that are not only contextually diverse but also resonate deeply with RPG conventions, indicating a significant advancement in interactive storytelling. This research not only reinforces the role of AI in augmenting game design but also underscores the broader potential of AI in creative content generation, marking a new era in the synergy between computational technology and artistic narrative creation. © 2023 IEEE.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Fossa Optimization Algorithm with Convolution Neural Network Based Brain Tumor Segmentation and Classification in MRI Images 3

Fossa Optimization Algorithm with Convolution Neural Network...

引用

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

作者： Veeresh Shivaprakash Hossain, Ramy Read Aruna, T.M. Kanth, Tatiraju.V.Rajani Sir M Visvesvaraya College of Engineering Raichur India Visvesvaraya Technological University Belagavi India Government Engineering College Raichur India College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq Nitte Meenakshi Institute of Technology Department of Artificial Intelligence and Machine Learning Bengaluru India Tvr Consulting Services Private Limited Gajularamaram Hyderabad India

ISBN: (纸本)9798331508456

Magnetic Resonance Image (MRI) brain tumor segmentation is critical and significant in a clinical field that assist in diagnosis, complete growth prediction and tumor mass rates required for patients. The complexity in segmenting brain tumors are challenging due to the various structures, shapes, locations, visual characteristics, frequency, texture and contrast. To overcome this issue, this research proposes a Fossa Optimization Algorithm (FOA) with Convolution Neural Network (CNN) for brain tumor classification. The Geodesic Active Contour (GAC) is used for segmentation which identifies tumor boundaries precisely in noisy and intricate data. FOA utilizes dynamic search strategy by its hunting behavior, balancing exploration and exploitation effectively. Its adaptive step size enables better convergence when avoiding local optima. Furthermore, its ability to capture edges and patterns makes it effective for classification. CNN are better to diverse in scale, noise and rotation because of its shared weights and local connectivity reduce the complexity thereby leading to higher accuracy and quick processing in classification. The FOA-CNN obtains 99.92% accuracy, 99.20% f1-score, 99.07% sensitivity and 99.34% precision for BRATS2020 dataset which is superior than Spatial Transformer Network and Non-local Attention Mechanism (STN-NAM). © 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

ECG and sEMG Conditioning and Wireless Transmission with a Biosignal Acquisition Board 3rd

ECG and sEMG Conditioning and Wireless Transmission with a B...

引用

3rd international conference on Optimization, learning Algorithms and Applications (OL2A)

作者： Luiz, Luiz E. Coutinho, Fabio R. Teixeira, Joao P. Inst Politecn Braganca Res Ctr Digitalizat & Intelligent Robot CeDRI Campus Santa Apolonia P-5300253 Braganca Portugal Univ Tecnol Fed Parana Campus Toledo BR-85902490 Curitiba Parana Brazil Inst Politecn Braganca Lab Sustentabilidade & Tecnol Reg Montanha SusTEC Campus Santa Apolonia P-5300253 Braganca Portugal

ISBN: (纸本)9783031530357;9783031530364

The market for Wearable Health Monitoring Systems (WHMS) has grown together with the demand for devices that offer greater medical reliability and lower cost. This study introduces a wearable system comprising conditioning blocks for electrocardiogram and surface electromyogram signals, an analog-to-digital converter, and wireless data transmission capabilities. These features have been implemented reliably in accordance with the specific requirements of these signals, as well as complying with patient safety directives and ensuring the quality of the resulting signal, allowing it to be used as a data collector for subsequent software implementation. To evaluate its performance, this system is compared against commercially available wearable devices, and the expected outcomes are examined. The obtained results are then presented, showcasing the system's capabilities and leading to a positive conclusion. As future work, there is a focus on enhancing the user interface and implement digital processing in the result for use in pathology recognition software with greater accuracy.

关键词： Electrocardiogram ECG Electromyogram EMG Surface Electromyogram sEMG signal Conditioning Wearable Health Monitoring Systems WHMS

来源：评论

学校读者我要写书评

暂无评论

Hand Gesture Recognition Using machine learning for Bionic Applications: Forearm Case Study 2nd

Hand Gesture Recognition Using Machine Learning for Bionic A...

引用

3rd international conference on Digital Technologies and Applications

作者： Lamsellak, Oussama Benlghazi, Ahmad Chetouani, Abdelaziz Benali, Abdelhamid ORAS Team LaMAO Lab Oujda 60000 Morocco Mohammed First Univ Oujda Elect & Syst Lab ENSA Oujda Oujda 60000 Morocco

ISBN: (纸本)9783031298561;9783031298578

The ubiquitous use of accelerometers and gyroscopes can provide meaningful knowledge about the recognition of human limb movements and offers significant potential for the design of human-machine interaction and the control of bionic systems. Our research puts an emphasis on linking acceleration data produced by hand movements to surface electromyograms (sEMG) collected in the arm in order to actively participate in robotic prosthesis control and the development of digital healthcare systems. The goal of this work is to demonstrate how to model a flexible system of hand gesture recognition using a dual-sensor accelerometer and gyroscope as a first stage, with the ability to evolve and improve its efficiency by incorporating other signals in subsequent stages of feature extraction and processing. Our research is primarily focused on identifying the triaxial signal generated via the accelerometer and gyroscope that appears when the hand is performing six gestures. Based on amassive gesture library collected over a long period of time by nine individuals belonging to three age categories and different genders, a forearm gesture classification model has been successfully developed, implementing a novel set of measurement criteria and statistical characteristics by virtue of five reputed machine-learning classifiers with an overall accuracy of 97.9% for training and 88.0% for testing, which are employed to differentiate and learn the forearm direction classes and interpret the performances.

关键词： Gesture Recognition machine learning Accelerometer EMG signals

来源：评论

学校读者我要写书评

暂无评论

Language Identification Based on Residual Network and Attention Mechanism 3

Language Identification Based on Residual Network and Attent...

引用

3rd international conference on Pattern Recognition and machine learning, PRML 2022

作者： Zeng, Ailing Ablimit, Mijit Hamdulla, Askar School of Information Science and Engineering Xinjiang University of China China Xinjiang Key Laboratory of Signal Detection and Processing Urumqi830017 China Xinjiang Key Laboratory of Multilingual Information Technology China

ISBN: (数字)9781665499507

ISBN: (纸本)9781665499507

Language identification process is necessary for the downstream tasks of cross lingual and multi-lingual application. This paper proposes a language recognition method based on ResNet-CA-BiGRU-Attention model. Firstly, the speech signal is converted into the corresponding spectrogram, and then the residual network is used for feature extraction according to the distribution of speech energy on the spectrogram. Coordinate Attention and Attention are used to highlight corelated features and suppress irrelevant features. In this paper, five languages are selected from the Common Voice data set. Experimental results show that the proposed language recognition method based on ResNet-CA-BiGRU-Attention model can effectively improve the performance of language recognition. © 2022 IEEE.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

Sub-system Integration and Health Dashboard for Autonomous Mobile Robots 3rd

Sub-system Integration and Health Dashboard for Autonomous M...

引用

3rd international conference on Optimization, learning Algorithms and Applications (OL2A)

作者： Franca, Andre Loures, Eduardo Jorge, Luisa Mendes, Andre Inst Politecn Braganca IPB Braganca Portugal Univ Tecnol Fed Parana UTFPR Curitiba Parana Brazil

ISBN: (纸本)9783031530357;9783031530364

Data visualization has become increasingly important to improve equipment monitoring, reduce operational costs and increase process efficiency with the ever-increasing amount of data being generated and collected in various fields. This paper proposes the development of a health monitoring system for an Autonomous Mobile Robot (AMR) that allows data acquisition and analysis for decision-making. The implementation of the proposed system showed favourable results in data acquisition, analysis, and visualization for decision-making. Through the use of a hybrid control architecture, the data acquisition and processing demonstrated efficiency without significant impact on battery consumption or resource usage of the AMR embedded microcomputer. The developed dashboard proved to be efficient in navigating and visualizing the data, providing important tools for the platform manager's decision-making. This work contributes to the health monitoring of devices based on Robot Operating System (ROS), which may be of interest to professionals and researchers in fields related to robotics and automation. Furthermore, the system presented will be open source, making it accessible and adaptable for use in different contexts and applications.

关键词： Human machine Interface Data visualization Autonomous Mobile Robot Robot Operating System Open Source Software

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73页 << < 8 9 10 11 12 13 14 15 16 17 > >>

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：