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

9,868 篇 会议
150 册 图书
134 篇 期刊文献

馆藏范围

10,152 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

7,056 篇 工学
- 5,683 篇 计算机科学与技术...
- 3,895 篇 软件工程
- 1,311 篇 信息与通信工程
- 1,279 篇 控制科学与工程
- 1,011 篇 电气工程
- 515 篇 生物工程
- 506 篇 机械工程
- 439 篇 生物医学工程（可授...
- 418 篇 电子科学与技术（可...
- 284 篇 光学工程
- 280 篇 交通运输工程
- 249 篇 化学工程与技术
- 244 篇 安全科学与工程
- 238 篇 仪器科学与技术
- 233 篇 动力工程及工程热...
- 187 篇 建筑学
2,671 篇 理学
- 1,603 篇 数学
- 573 篇 生物学
- 548 篇 物理学
- 484 篇 统计学（可授理学、...
- 369 篇 系统科学
- 230 篇 化学
2,156 篇 管理学
- 1,293 篇 管理科学与工程(可...
- 1,045 篇 图书情报与档案管...
- 661 篇 工商管理
435 篇 医学
- 390 篇 临床医学
- 297 篇 基础医学(可授医学...
- 173 篇 药学(可授医学、理...
261 篇 教育学
- 250 篇 教育学
251 篇 法学
- 210 篇 社会学
159 篇 经济学
97 篇 农学
18 篇 文学
11 篇 军事学
7 篇 艺术学

主题

230 篇 data mining
206 篇 knowledge engine...
186 篇 feature extracti...
166 篇 artificial intel...
166 篇 intelligent syst...
161 篇 semantics
159 篇 neural networks
152 篇 knowledge based ...
130 篇 computational mo...
113 篇 decision making
105 篇 deep learning
101 篇 predictive model...
101 篇 visualization
95 篇 optimization
92 篇 real-time system...
92 篇 humans
92 篇 information retr...
91 篇 software enginee...
91 篇 machine learning
89 篇 intelligent agen...

机构

37 篇 school of inform...
37 篇 ieee
33 篇 college of infor...
24 篇 southwest jiaoto...
24 篇 school of inform...
20 篇 research team on...
20 篇 fujian provincia...
17 篇 faculty of infor...
17 篇 school of inform...
15 篇 de la salle univ...
15 篇 college of compu...
14 篇 school of inform...
14 篇 school of inform...
14 篇 department of bu...
13 篇 university of ch...
13 篇 de la salle univ...
12 篇 institutes for r...
11 篇 faculty of robot...
11 篇 jilin engineerin...
11 篇 school of mechat...

作者

25 篇 robert j. howlet...
23 篇 pan jeng-shyang
18 篇 yang xu
18 篇 tsuda kazuhiko
17 篇 chang kuo-chi
17 篇 królikowski toma...
15 篇 jain lakhmi c.
15 篇 salabun wojciech
15 篇 wieckowski jakub
15 篇 jain lakhmi
13 篇 li tianrui
12 篇 aoe jun-ichi
12 篇 chehri abdellah
12 篇 yajima kuniaki
11 篇 atlam el-sayed
11 篇 bandala argel
11 篇 watada junzo
10 篇 zou li
10 篇 chamier-gliszczy...
10 篇 fuketa masao

语言

9,897 篇 英文
207 篇 其他
58 篇 中文
2 篇 葡萄牙文

检索条件"任意字段=13th International Conference on Knowledge-Based Intelligent Information and Engineering Systems"

共 10152 条记录，以下是71-80 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：

IOT and developed deep learning based road accident detection system and societal knowledge management 2nd

IOT and developed deep learning based road accident detectio...

引用

2nd international conference on Next-Generation Computing and information systems, ICNGCIS 2023

作者： Ananth, K.R. Fayaz Khan, Sarfraz Agarwal, Abhishek Wasim Bhatt, Mohammed Murtaza Alvi, Ahmad Degadwala, Sheshang Nandha Arts and Science College Tamil Nadu Erode India SAT – Algonquin College Ottawa Canada Vermont State University United States Model Institute of Engineering and Technology J&K Jammu India College of Finance Department of Business Administration Saudi Electronic University Riyadh Saudi Arabia Department of Computer Engineering Sigma University Gujarat Vadodara India

ISBN: (纸本)9781032738659

Business organizations and the research community try to precisely detect occurrences and assist in the case of a disaster. Most development systems are hardware-based, making them pricey and unavailable in every vehicle. A vehicle’s sensors can be destroyed in various ways, including minor accidents or fixed interactions. In instances, the sensors are incapable of detecting an accident. intelligent phone sensors are a great alternative because of their dependability and availability. the study involves creating a smartphone application that continually reads sensor data and sends it to the cloud. the crash is discovered by threshold analysis. the critical novelty of this research is creating a scheme that alerts nearby hospitals and ambulances when an accident occurs. the system will have more minor inaccuracies, precisely identify accidents, and perform better than earlier techniques using four sensory inputs. this paper introduced novel types of deep learning for accident detection. © 2025 the Author(s).

关键词： knowledge management

来源：评论

学校读者我要写书评

暂无评论

A Cross-Scale Multi-Branch Feature Fusion based Method for Smoke and Fire Detection in Warehouses 24

A Cross-Scale Multi-Branch Feature Fusion Based Method for S...

引用

13th international conference on Computing and Pattern Recognition, ICCPR 2024

作者： Bai, Yanbing Liu, Pengyu Liu, Weilong Deng, Yiyang Kong, Lili Chen, Shanji Chen, Jiali Yuan, Bowen School of Information Science and Technology Beijing Laboratory of Advanced Information Networks Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing University Of Technology Beijing China Information Technology Co. Ltd Dingzhou China Beijing-Dublin International College at BJUT Beijing University Of Technology Beijing China College of Physics and Electronic Information Engineering Qinghai Minzu University Qinghai China

ISBN: (纸本)9798400717482

To address the challenges of leakage, misdetection, and low accuracy caused by environmental complexity, object occlusion, and insufficient lighting in smoke and fire detection within warehouse scenarios, this paper proposes a cross-scale multi-branch feature fusion network for smoke and fire detection, named SF-YOLO. Firstly, a multi-branch feature enhancement module, Res2Net-C, is proposed to introduce an attention mechanism using a multi-branch feature fusion network, which not only extends the sensory field of the network, but also enhances the ability of extracting effective information, while effectively suppressing the interference of irrelevant information. It effectively improves detection performance under complex environmental conditions and in the presence of object occlusion. Secondly, a cross-scale feature fusion network structure, MSFPN, is proposed, which achieves effective complementation and fusion of high-level and low-level information by establishing hopping connections between features at different scales, and significantly improves the recognition accuracy of the type and location of the smoke and fire in low-light conditions. In addition, the added small target detection layer further improves the network's ability to detect small targets. Finally, in order to better adapt to pyrotechnic targets with variable morphology, EIoU is adopted as the bounding box loss function. Test results on a self-built dataset show that SF-YOLO achieves a mean accuracy rate (mAP) of 87.5% in the task of detecting smoke and fire under multiple environmental factors in a warehouse scenario, proving its effectiveness and usefulness. © 2024 Copyright held by the owner/author(s).

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Hand Gesture Recognition Method based on mmWave Radar with MobileViT and knowledge Distillation 16

Hand Gesture Recognition Method based on mmWave Radar with M...

引用

16th international conference on Signal Processing systems, ICSPS 2024

作者： Zhang, Xiangqun Ge, Zhizhou Lu, Kai Du, Genyuan Shen, Jiawen Gao, Xiangqian School of Information Engineering Xuchang University Xuchang461000 China Henan International Joint Laboratory of Polarization Sensing and Intelligent Signal Processing Xuchang461000 China Henan Shengshi Hengxin Technology Co. Ltd Xuchang461111 China

ISBN: (纸本)9781510689251

Human-hand gesture recognition using millimetre wave radar is attractive in human-computer interfaces, industrial Internet of things, and smart home. However, the existing CNN or RNN model is so complex and large that it is hard to apply to mobile vision tasks and embedded devices. this paper proposes dual lightweight convolutional neural networks, MobileViT and knowledge distillation, to solve this problem. Firstly, we acquire the original radar echoes of frequency-modulated continuous wave (FWCW) signal and reshape the three-dimensional matrix by Chirps * Samples * Frames. then, we perform the signal processing method to eliminate the noise and static background. Secondly, we employ the Fast Fourier Transform to extract the hand gestures feature map of distance and Doppler information. Finally, the feature map is input into the modified MobileViT to recognize dynamic hand gestures, and knowledge distillation models is used to simplify the model structure. the experimental results show that the parameter space complexity of the constructed model is reduced to 0.018 M, and the computational complexity is 0.082 GFLOPs after knowledge distillation *** method is verified in 12 complex gesture. It has the potential to be applied in mobile tasks and embedded devices. © 2025 SPIE.

关键词： Fast Fourier transforms

来源：评论

学校读者我要写书评

暂无评论

Effective knowledge Graph Embedding with Quaternion Convolutional Networks 13th

Effective Knowledge Graph Embedding with Quaternion Convolut...

引用

13th international conference on Natural Language Processing and Chinese Computing

作者： Liang, Qiuyu Wang, Weihua Yu, Lie Bao, Feilong Inner Mongolia Univ Coll Comp Sci Hohhot Peoples R China Natl & Local Joint Engn Res Ctr Intelligent Infor Hohhot Peoples R China Inner Mongolia Key Lab Multilingual Artificial In Hohhot Peoples R China Natl Univ Def Technol Coll Comp Sci Changsha Peoples R China

ISBN: (纸本)9789819794362;9789819794379

Convolutional Neural Networks (CNNs) have demonstrated effectiveness in knowledge graph embedding, but existing CNN-based methods encounter two main challenges. Firstly, CNN-based models with simple architectures are unable to extract latent features. Secondly, these models enhance feature extraction by adding extra modules, which inevitably increases training cost with limited performance improvement. To address these challenges, we go beyond traditional CNNs and propose a novel knowledge graph embedding model, which utilizes the powerful capability of Quaternion Convolutional Neural Networks (QCNNs) for effective representation learning. Specifically, we learn representations of entities and relations in a quaternion space and utilize QCNN to extract the inherent information of the entity-relation matrix. We evaluate the performance of our model on multiple knowledge graph completion benchmark datasets. Experimental results show that our model achieves effective improvements compared to existing CNN-based models. Moreover, in terms of training time, our model is faster than other outstanding models. the code of all experiments is available at https://***/llqy123/ConvQE.

关键词： Quaternion algebra knowledge graph embedding Link prediction Convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

Revision of a Smart Factory Software Architecture from Monolith to Microservices 2nd

Revision of a Smart Factory Software Architecture from Monol...

引用

28th international conference on Enterprise Design Operations and Computing

作者： Seiger, Ronny Malburg, Lukas Univ St Gallen Inst Comp Sci CH-9000 St Gallen Switzerland Univ Trier Artificial Intelligence & Intelligent Informat Sy D-54296 Trier Germany Branch Univ Trier German Res Ctr Artificial Intelligence DFKI Behringstr 21 D-54296 Trier Germany

ISBN: (纸本)9783031790584;9783031790591

Software architecture plays an important role in the development of modern, complex software systems as it influences a system's quality attributes and ability to grow with future demand. Designing the software architecture of cyber-physical systems (CPS) becomes even more challenging due to their capability of directly influencing the physical world and thus introducing new non-functional requirements related to fault-tolerance, safety, and resource scarcity. Existing research focuses on systems engineering to achieve the vertical integration of CPS with an organization's information systems and processes, but not on software architecture to horizontally extend existing systems with new CPS. In this report we describe the process of revising an existing monolithic software architecture for a smart factory towards a microservices-based architecture to meet these new requirements and prepare the factory to be extended with new CPS. For the revision of the existing architecture, we provide an analysis of its code base before and after changes, a description of the refactoring process, and discuss relevant new non-functional requirements and architecture options. We elaborate on the architectural decisions favoring microservices and analyze the new architecture regarding improved quality attributes to evaluate the system.

关键词： Cyber-physical systems Software Architecture Internet of things Microservices Industry 4.0

来源：评论

学校读者我要写书评

暂无评论

25th international conference on intelligent Data engineering and Automated Learning, IDEAL 2024

25th International Conference on Intelligent Data Engineerin...

引用

25th international conference on intelligent Data engineering and Automated Learning, IDEAL 2024

ISBN: (纸本)9783031777370

the proceedings contain 92 papers. the special focus in this conference is on intelligent Data engineering and Automated Learning. the topics include: Model-based Meta-reinforcement Learning for Hyperparameter Optimization;towards Sustainable Precision: Machine Learning for Laser Micromachining Optimization;association Rules Mining with Auto-encoders;using Contrastive Learning to Map Stylistic Similarities in Narrative Writers;automatic Classification of Signal and Noise in Functional Magnetic Resonance Imaging Scans Using Convolutional Neural Networks;how Resilient are Language Models to Text Perturbations?;emotional Sequential Influence Modeling on False information;CSSDH: An Ontology for Social Determinants of Health to Operational Continuity of Care Data Interoperability;padel Two-Dimensional Tracking Extraction from Monocular Video Recordings;drowsiness Detection Using Vital Sign Sensors and Deep Learning on Smartwatches;Benchmarking Out of the Box Open-Source LLMs for Malware Detection based on API Calls Sequences;multimodal Visio-Lingual Content Analysis to Detect Fake Content on Reddit;MetaLIRS: Meta-learning for Imputation and Regression Selection;pipeline for Semantic Segmentation of Large Railway Point Clouds;preliminary Investigation on Machine Learning and Deep Learning Models for Change of Direction Classification in Running;efficient Radar Scheduling Using Genetic Algorithms and Stochastic Heuristic Initialization;towards a Communication Specification Language for Heterogeneous Service Orchestration based on Process Calculus and Holonic Multi-agent systems;counterfactual Explanations for Sustainable Tourism Indicators;Tracking Healthy Organs in Medical Scans to Improve Cancer Treatment by Using UW-Madison GI Tract Image Segmentation;low Consumption Models for Disease Diagnosis in Isolated Farms;fast and Scalable Recommendation Retrieval Model with Mixed Attention and knowledge Distillation;Federated Learning for Vietnamese SMS Spam Detection Using Pre

关键词：

来源：评论

学校读者我要写书评

暂无评论

25th international conference on intelligent Data engineering and Automated Learning, IDEAL 2024

25th International Conference on Intelligent Data Engineerin...

引用

25th international conference on intelligent Data engineering and Automated Learning, IDEAL 2024

ISBN: (纸本)9783031777301

关键词：

来源：评论

学校读者我要写书评

暂无评论

Energy-Guided Topology Mamba for EEG-based BCI 13

Energy-Guided Topology Mamba for EEG-based BCI

引用

13th international Winter conference on Brain-Computer Interface, BCI 2025

作者： Jeong, Seungwoo Jeon, Jaehyun Suk, Heung-Il The Department of Artificial Intelligence Korea University Seoul02841 Korea Republic of The Department of Artificial Intelligence The Department of Brain and Cognitive Engineering Korea University Seoul02841 Korea Republic of

ISBN: (纸本)9798331521929

Electroencephalography (EEG) signals, widely used in neuroscience and clinical research, provide non-invasive insights into brain activity. However, their high variability, noise, and complex spatiotemporal dynamics present significant challenges for effective modeling. To tackle these issues, we introduce an energy-guided topology for EEG signal analysis within the Mamba framework, designed to enhance feature propagation by leveraging spectral energy distribution. Our method first transforms EEG signals into the frequency domain and constructs an energy-based topology using channel-wise spectral power. Features are then propagated bidirectionally along energy gradients, enabling the Mamba model to capture temporal and spatial dependencies more effectively. By aligning feature learning with energy flow in the frequency domain, our approach improves the efficiency and accuracy of EEG modeling. Experimental results on the public dataset demonstrate that our method outperforms CNN-based, Transformer-based, and vanilla Mamba models, underscoring its potential to advance EEG signal processing. © 2025 IEEE.

关键词： Frequency domain analysis

来源：评论

学校读者我要写书评

暂无评论

Personalized Continual EEG Decoding: Retaining and Transferring knowledge 13

Personalized Continual EEG Decoding: Retaining and Transferr...

引用

13th international Winter conference on Brain-Computer Interface, BCI 2025

作者： Li, Dan Shin, Hye-Bin Yin, Kang Dept. of Artificial Intelligence Korea University Seoul Korea Republic of Dept. of Brain and Cognitive Engineering Korea University Seoul Korea Republic of

ISBN: (纸本)9798331521929

the significant inter-subject variability in electroencephalogram (EEG) signals often results in substantial changes to neural network weights as data distributions shift. this variability frequently causes catastrophic forgetting in continual EEG decoding tasks, where previously acquired knowledge is overwritten as new subjects are introduced. While retraining the entire dataset for each new subject can mitigate forgetting, this approach imposes significant computational costs, rendering it impractical for real-world applications. therefore, an ideal brain-computer interface (BCI) model should incrementally learn new information without requiring complete retraining, thereby reducing computational overhead. Existing EEG decoding methods typically rely on large, centralized source-domain datasets for pre-training to improve model generalization. However, in practical scenarios, data availability is often constrained by privacy concerns. Furthermore, these methods are susceptible to catastrophic forgetting in continual EEG decoding tasks, significantly limiting their utility in long-term learning scenarios. To address these issues, we propose the Personalized Continual EEG Decoding (PCED) framework for continual EEG decoding. the framework uses Euclidean Alignment for fast domain adaptation, reducing inter-subject variability. To retain knowledge and prevent forgetting, it includes an exemplar replay mechanism that preserves key information from past tasks. A reservoir sampling-based memory management strategy optimizes exemplar storage to handle memory constraints in long-term learning. Experiments on the OpenBMI dataset with 54 subjects show that PCED balances knowledge retention and classification performance, providing an efficient solution for real-world BCI applications. © 2025 IEEE.

关键词： Memory management

来源：评论

学校读者我要写书评

暂无评论

Automatic Pain Assessment based on Physiological Signals: Application of Multi-Scale Networks and Cross-Attention Cross-Attention 24

Automatic Pain Assessment Based on Physiological Signals: Ap...

引用

13th international conference on Bioinformatics and Biomedical Science, ICBBS 2024

作者： Li, JiaHao Luo, JinCheng Wang, YanSheng Jiang, YunXiang Chen, Xu Quan, YuJuan School of Information Science and Technology Jinan University GuangDong GuangZhou China School of Intelligent Science and Engineering Jinan University GuangDong ZhuHai China International School Jinan University GuangDong GuangZhou China School of Management Jinan University GuangDong GuangZhou China

ISBN: (纸本)9798400717956

Pain is a subjective feeling closely linked to physiology and psychology. When pain occurs, it will arouse people's attention to physical threats and is closely related to disease and survival. the most common method of assessing pain is self-reporting. However, in the case of non-communicative patients, self-assessment of pain is not feasible and must be to rely on observer reports. Observer reports of pain may be inaccurate due to subjective biases and cognitive differences observers. Furthermore, it is impractical to conduct continuous monitoring by self-reporting and observer reports. therefore, automatic pain assessment technology can be used to assist human caregivers and supplement their services, th ereby improving the quality of pain management. In this study, we designed and implemented an innovative pain assessment model, which we call EDAPainNet. the model uses skin electrodermal signals (EDA) for pain assessment. the model structure includes multi-size window dimension convolutional network (MSWDCN), activate channels feature network (ACFN) and temporal convolutional cross attention network (TCCAN), which aim to extract and optimize key features from EDA signals and ensure the accuracy of feature representation. We validated our model on the public dataset BioVid. Experiments showed that our model can output pain levels more accurately than existing methods, providing an efficient and reliable automated solution for pain assessment. the BioVid pain dataset evaluation reveals that our method outshines existing approaches, achieving an impressive recognition accuracy of 81.25% for distinguishing between painless and painful states. In comparative experiments, our method has demonstrated a notable improvement of over 2% in performance. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Physiological models

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 << < 4 5 6 7 8 9 10 11 12 13 > >>

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：