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

302 篇 会议
9 册 图书
1 篇 期刊文献

馆藏范围

312 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

223 篇 工学
- 189 篇 计算机科学与技术...
- 132 篇 软件工程
- 39 篇 控制科学与工程
- 37 篇 信息与通信工程
- 25 篇 生物工程
- 18 篇 光学工程
- 17 篇 生物医学工程（可授...
- 13 篇 电气工程
- 11 篇 安全科学与工程
- 8 篇 机械工程
- 8 篇 化学工程与技术
- 8 篇 交通运输工程
- 5 篇 仪器科学与技术
- 5 篇 动力工程及工程热...
- 5 篇 环境科学与工程（可...
82 篇 理学
- 29 篇 物理学
- 28 篇 数学
- 27 篇 生物学
- 14 篇 统计学（可授理学、...
- 8 篇 化学
- 8 篇 系统科学
46 篇 管理学
- 25 篇 管理科学与工程(可...
- 23 篇 图书情报与档案管...
- 13 篇 工商管理
18 篇 法学
- 18 篇 社会学
16 篇 医学
- 16 篇 临床医学
- 14 篇 基础医学(可授医学...
- 8 篇 药学(可授医学、理...
- 7 篇 公共卫生与预防医...
6 篇 教育学
- 6 篇 教育学
1 篇 经济学
1 篇 文学
1 篇 农学

主题

32 篇 human computer i...
8 篇 ubiquitous compu...
8 篇 human-computer i...
8 篇 affective comput...
7 篇 deep learning
7 篇 emotion recognit...
6 篇 machine learning
6 篇 user interfaces ...
6 篇 accuracy
6 篇 convolutional ne...
5 篇 gesture recognit...
5 篇 cloud computing
5 篇 computer vision
4 篇 intelligent agen...
4 篇 computer communi...
4 篇 face recognition
4 篇 eeg
4 篇 virtual reality
3 篇 e-learning
3 篇 electroencephalo...

机构

4 篇 china electronic...
4 篇 school of comput...
3 篇 south china univ...
3 篇 sharda universit...
3 篇 guangdong electr...
3 篇 school of comput...
2 篇 school of comput...
2 篇 mechanical elect...
2 篇 university insti...
2 篇 computer school ...
2 篇 kindi center for...
2 篇 engineering rese...
2 篇 univ twente huma...
2 篇 center for lingu...
2 篇 china electronic...
2 篇 school of comput...
2 篇 language technol...
2 篇 raj kumar goel i...
2 篇 school of biolog...
2 篇 catarc intellige...

作者

6 篇 nijholt anton
4 篇 pantic maja
3 篇 sun xiaofan
2 篇 valstar michel
2 篇 zhou jing
2 篇 tareq ahram
2 篇 sharma aman kuma...
2 篇 erhan dai
2 篇 jining li
2 篇 redha taiar
2 篇 wang qing
2 篇 nishida toyoaki
2 篇 singh jagendra
2 篇 poelman wim
2 篇 luyang li
2 篇 wu kai
2 篇 juan carlos augu...
2 篇 feng zhiquan
2 篇 vyas dhaval
2 篇 dai erhan

语言

299 篇 英文
11 篇 其他
4 篇 中文

检索条件"任意字段=4th International Conference on Intelligent Computing and Human-Computer Interaction, ICHCI 2023"

共 312 条记录，以下是1-10 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：

2023 4th international conference on intelligent computing and human-computer interaction, ichci 2023

2023 4th International Conference on Intelligent Computing a...

引用

4th international conference on intelligent computing and human-computer interaction, ichci 2023

ISBN: (纸本)9798350343113

the proceedings contain 84 papers. the topics discussed include: YONA: an intelligence question-answering system based on artificial intelligence;a hybrid model based on GAT and TAGCN for node classification;SRGCN: social relationship graph convolutional network-based social network user geolocation prediction;dense pedestrian detection method based on improved YOLOv5;opening the black box: interpretable machine learning reveals the relationship between lexical diversity and writing quality;porting and optimization of electric power consumers anomaly behavior monitoring on ARM platform;short text similarity detection based on graph attention networks and knowledge augmentation;MSFF-Net: a multi-scale feature fusion network for hippocampus segmentation;research on path optimization of automated warehouse based on genetic algorithm;and modeling operational profile for ai systems: a case study on UAV systems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

2023 4th international conference on intelligent computing and human-computer interaction

2023 4th International Conference on Intelligent Computing a...

引用

intelligent computing and human-computer interaction (ichci), international conference on

2023 4th international conference on intelligent computing and human-computer interaction.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Music Recommender System to Identify the Emotional State of a Person Using Machine Learning Algorithms 4

A Music Recommender System to Identify the Emotional State o...

引用

4th international conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Muruganantham, A. Malarvizhi, C. Divya Vahini, S. Saranya, D. Uthiramoorthy, A. Karnataka Bengaluru India Psg Institute of Advanced Studies Department of Computer Science Coimbatore India Dr.Mahalingam College of Engineering and Technology Department of Computer Applications Tamil Nadu Pollachi India Sri Eshwar College of Engineering Department of Information Technology Coimbatore India Rathinam College of Arts and Science Department of Computer Science India

ISBN: (纸本)9798331523923

In today's digital world, customized recommendation algorithms can improve user experiences in many different areas. Within the sphere of intelligent human-technology interaction, this paper specifically examines a music recommender system driven by machine learning algorithms. It figures out what mood users are in and can provide an appropriate response in real time. the system being propounded in this essay uses advanced technology in facial expression recognition. With the help of a webcam, it aims to accurately detect user emotions, including joy, sadness, and anger. Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) and Support Vector Machines (SVM) have been employed to effectively classify people's mood and recommend an appropriate song. Our extensive tests and examinations show that CNN, RNN, and SVM models are all very good at guessing users' moods - with high precision, recall, F1-score, and accuracy percentages. Furthermore, in-depth analyses like confusion matrixes illuminate how well each model serves as an emotion recognizer. this study's findings are representative of future prospects in affective computing around the globe with major implications for intelligent recommendation systems to which it's important that the models are sensitive. In conclusion, the suggested Music Recommender System is something new for taking a more personal view: We can be as deeply entertained as the web allows us to be - make tailored entertainment paths in the digital era. © 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

IPDD: intelligent Parkinson Disease Detection System 4th

IPDD: Intelligent Parkinson Disease Detection System

引用

4th international conference on Smart IoT Systems: Innovations and computing, SSIC 2023

作者： Singhal, Manish Tiwari, Vinita Sharma, Ashish Electronic and Communication Indian Institute of Information Technology Rajasthan Kota325003 India Computer Science and Engineering Manipal University Rajasthan Jaipur303007 India

ISBN: (纸本)9789819751990

Worldwide, millions of peoples are affected by complex neuro degenerative disorder, that is known as PD (Parkinson Disease). In recent years, it is very critical for accurate diagnosis of PD at early stage for implementing timely interventions and improving patient life. there have been growing interest in developing intelligent systems for Parkinson’s disease detection, harnessing the potential of cutting-edge technologies such as artificial intelligence, machine l earning, and sensor-based data analysis. this research paper presents an in-depth exploration of an intelligent Parkinson Disease Detection System (IPDDS) designed for early diagnosis and quality level monitoring of PD using two most accurate machine learning techniques—SVM and Random Forest. the presented work relates the use of various performance metrices like Accuracy, Confusion Matrix, Precision, etc. Standard Dataset having voice samples of human’s having Parkinson Disease and not having PD is used to validate the various performance parameters and predict the PD or non-PD. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Neurodegenerative diseases

来源：评论

学校读者我要写书评

暂无评论

GCN Rewarded Reinforcement Learning for Action Segmentation 24

GCN Rewarded Reinforcement Learning for Action Segmentation

引用

4th international Joint conference on Robotics and Artificial Intelligence, JCRAI 2024

作者： Wang, Liangliang Liu, Jiayao Hu, Xujun Huo, Guanglei Wuhan University of Technology Wuhan China Beijing Jiaotong University Beijing China Institute of Advanced Manufacturing Technology Fujian Key Laboratory of Intelligent Operation and Maintenance Robot Technology Quanzhou China

ISBN: (纸本)9798400710100

Action recognition is a very basic topic for human-robot visual interaction. To enable action recognition for real-world applications, at the core is the problem of action segmentation, which aims to segment action slices from long videos. Existing action segmentation approaches rely heavily on hand-crafted techniques, which are limited on accuracy due to the spatio-temporal complexity of actions across videos. To this end, we formulate action segmentation as a Markov decision process rewarded by observing the action recognition results, and build a reinforcement learning framework to adjust the segmenting procedure iteratively according to the rewards. In particular, to perceive the segmented actions for reinforcement learning, we propose a temporal graph convolutional network (GCN) by representing the context relationships of neighboring action slices, whose states are initialized by considering the consistency of actions, and updated by computing their temporal similarity fusing the tIoU and center distance. Convolutional neural network (CNN) backbone features are used as the nodes of GCN, and the edges of GCN are calculated utilizing the context relationships for spatially and temporally representation. By designing an observation and objective module within the reinforcement learning framework based on GCN representations, we finish the network training for. Finally, we conduct extensive experiments on two public datasets, and by comparisons with some state-of-the-art results, our method is demonstrated. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

E-Healthcare Record System Using Blockchain 4th

E-Healthcare Record System Using Blockchain

引用

4th international conference on Smart IoT Systems: Innovations and computing, SSIC 2023

作者： Pattnayak, Parthasarathi Mohanty, Arpeeta Das, Tulip Patnaik, Sanghamitra School of Computer Applications KIIT Deemed to Be University Odisha Bhubaneswar India Faculty of Emerging Technologies SRI SRI University Odisha Cuttack India School of Law KIIT Deemed to Be University Odisha Bhubaneswar India

ISBN: (纸本)9789819751990

the term "Electronic Healthcare Record" (EHR) refers to an electronic recording of the medical record of a patient that is maintained by the system over time and can include all relevant, authoritative clinical information important to the user’s care. All of the patient’s medical data (also called PHI) about the diagnosis of disease along with diagnostic reports is saved and communicated across the system’s users within a contemporary, stored in the cloud E-healthcare system. But a significant concern is the protection of these private documents from misuse and unauthorized access. In this situation, the blockchain-based record-sharing solution might be crucial for safe medical data exchange. In this paper we discussed the session data will be encrypted using intelligent deals with between planetary file solution (IPFS)-based secured healthcare picture security solution. For improved accountability, it also logs each health care interaction in the blockchain. For healthcare services, this cutting-edge paradigm offers significant adaptability and EHR accessibility. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

human Action Recognition Using Mediapipe Holistic Keypoints: A Deep Learning Approach 4th

Human Action Recognition Using Mediapipe Holistic Keypoints:...

引用

4th international conference on Advanced Network Technologies and intelligent computing, ANTIC 2024

作者： Shandilya, Utkarsh Sharma, Vijeta Mishra, Deepti Department of Computer Science and Engineering Central University of Haryana Haryana India NTNU-Norwegian University of Science and Technology Gjøvik2815 Norway

ISBN: (纸本)9783031837951

human action recognition (HAR) is a crucial field in computer vision with applications ranging from video surveillance to human-computer interaction. this study explores an efficient framework for HAR by leveraging human keypoint extraction using Google’s Mediapipe and Long Short-Term Memory (LSTM) networks. the Mediapipe framework provides accurate and real-time human keypoint extraction, significantly reducing the computational complexity associated with raw video data processing. these keypoints, representing skeletal movements, are utilised as input to LSTM networks, which capture the temporal dependencies vital for action classification. the proposed method is evaluated on two benchmark datasets: UCF101 and Kinetics 400. UCF101 contains 13,320 video clips across 101 action classes, while Kinetics 400 features 400 human action categories. the combination of Mediapipe for feature extraction and LSTM for temporal modelling achieves 92.40% and 86.8% accuracy on UCF101 and Kinetics400, respectively. the results demonstrate the effectiveness of keypoint-based approaches for HAR. this study highlights the potential of lightweight, real-time human action recognition frameworks suitable for resource-constrained environments, especially for edgeAI and edge Robotics. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

A Music Recommender System to Identify the Emotional State of a Person Using Machine Learning Algorithms

A Music Recommender System to Identify the Emotional State o...

引用

Sentiment Analysis and Deep Learning (ICSADL), international conference on

作者： Muruganantham A C. Malarvizhi Divya Vahini. S D. Saranya A. Uthiramoorthy Department of Computer Science (PG) Kristu Jayanti College Bengaluru Karnataka India Department of Computer Science PSG Institute of Advanced Studies Coimbatore India Department of Computer Applications Dr.Mahalingam College of Engineering and Technology Pollachi Tamil Nadu India Department of Information Technology Sri Eshwar College of Engineering Coimbatore Department of Computer Science Rathinam College of Arts and Science

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

In today's digital world, customized recommendation algorithms can improve user experiences in many different areas. Within the sphere of intelligent human-technology interaction, this paper specifically examines a music recommender system driven by machine learning algorithms. It figures out what mood users are in and can provide an appropriate response in real time. the system being propounded in this essay uses advanced technology in facial expression recognition. With the help of a webcam, it aims to accurately detect user emotions, including joy, sadness, and anger. Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) and Support Vector Machines (SVM) have been employed to effectively classify people's mood and recommend an appropriate song. Our extensive tests and examinations show that CNN, RNN, and SVM models are all very good at guessing users' moods--with high precision, recall, F1-score, and accuracy percentages. Furthermore, in-depth analyses like confusion matrixes illuminate how well each model serves as an emotion recognizer. this study's findings are representative of future prospects in affective computing around the globe with major implications for intelligent recommendation systems to which it's important that the models are sensitive. In conclusion, the suggested Music Recommender System is something new for taking a more personal view: We can be as deeply entertained as the web allows us to be--make tailored entertainment paths in the digital era.

关键词： Support vector machines Emotion recognition Recurrent neural networks Machine learning algorithms Accuracy Mood Face recognition Computational modeling Convolutional neural networks Recommender systems

来源：评论

学校读者我要写书评

暂无评论

A Novel intelligent Traffic Control System for Identifying Traffic Congestion and Emergency Vehicle Detection in Malaysia 4th

A Novel Intelligent Traffic Control System for Identifying T...

引用

4th international conference on Internet of things, ICIoT 2023

作者： Omar, Mas Yakub, Fitri Niranjana, Govindan Azizan, Azizul Liana, Farah Suseela, G. Malaysia-Japan International Institute of Technology Universiti Teknologi Malaysia Kuala Lumpur54100 Malaysia School of Computing SRM Institute of Science and Technology Tamil Nadu Kattankulathur 603203 India Razak Faculty of Technology and Informatics Universiti Teknologi Malaysia Kuala Lumpur54100 Malaysia

ISBN: (纸本)9783031856655

Traffic congestion is a community-related issue in urban areas associated with the ease and comfort of road travel. this problem persists in Malaysia, owing to the fast expansion of urban areas caused by increased vehicle volume due to rapid human population growth. Amid traffic congestion, an emergency vehicle must travel smoothly to cater for emergency action to save human life. Existing traffic signal systems are unsuccessful at solving emergency vehicles stranded during traffic congestion since they are time-based, resulting in the worst travel times and energy loss. therefore, this study is inspired to provide a novel IoT system utilising Raspberry Pi and Arduino that enables the emergency vehicle to act as the input to the traffic light to guide it through congested intersection roads that require immediate passing. the "Traffic Control Module," the system’s central control unit, controls the traffic signal colour-switching action to realise this study’s intelligent traffic control system objective. It promotes scalability in the design. However, the system faces some limitations potentially related to the system algorithm and hardware limitations regarding its performance on vehicle detection accuracy. the paper also discusses potential future improvements, which can enhance the system to serve the community better. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

Research on Information Fusion Interface of human-computer interaction based on Mixed Reality Technology 4

Research on Information Fusion Interface of Human-Computer I...

引用

4th international conference on intelligent computing and human-computer interaction, ichci 2023

作者： Zhu, Yeshan Wang, Wei Jiao, Haoyang Air and Missile Defense College Air Force Engineering University Xi'an China

ISBN: (纸本)9798350343113

In order to solve the problem that high-dimensional mixed reality interface brings low task performance and heavy cognitive load to users in cross-layer operation, we study the information fusion interface of human-computer interaction and propose two kinds of fusion interfaces. the experimental results show that the deep fusion interface performs better than the combined interface in cognitive difficulty, cognitive load, operational efficiency and subjective evaluation. the research conclusion can guide the design of human-computer interaction interface in mixed reality. © 2023 IEEE.

关键词： Mixed reality

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32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：