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

1,750 篇 会议
76 册 图书
48 篇 期刊文献

馆藏范围

1,873 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

1,276 篇 工学
- 1,063 篇 计算机科学与技术...
- 564 篇 软件工程
- 213 篇 电气工程
- 213 篇 信息与通信工程
- 211 篇 控制科学与工程
- 103 篇 生物工程
- 90 篇 光学工程
- 81 篇 生物医学工程（可授...
- 76 篇 机械工程
- 57 篇 交通运输工程
- 51 篇 电子科学与技术（可...
- 44 篇 安全科学与工程
- 40 篇 化学工程与技术
- 32 篇 仪器科学与技术
- 24 篇 材料科学与工程（可...
- 21 篇 动力工程及工程热...
- 21 篇 建筑学
430 篇 理学
- 193 篇 数学
- 182 篇 物理学
- 121 篇 生物学
- 63 篇 统计学（可授理学、...
- 42 篇 系统科学
- 34 篇 化学
205 篇 管理学
- 116 篇 管理科学与工程(可...
- 105 篇 图书情报与档案管...
- 42 篇 工商管理
91 篇 医学
- 76 篇 临床医学
- 33 篇 基础医学(可授医学...
- 16 篇 药学(可授医学、理...
28 篇 法学
- 26 篇 社会学
15 篇 教育学
8 篇 农学
7 篇 经济学
7 篇 文学
3 篇 艺术学
2 篇 军事学

主题

244 篇 pattern recognit...
93 篇 real-time system...
91 篇 feature extracti...
83 篇 accuracy
77 篇 artificial intel...
55 篇 face recognition
55 篇 intelligent syst...
54 篇 training
49 篇 deep learning
44 篇 speech recogniti...
41 篇 neural networks
41 篇 machine learning
40 篇 pattern recognit...
38 篇 computer imaging...
38 篇 convolutional ne...
37 篇 object detection
36 篇 learning systems
35 篇 support vector m...
35 篇 object recogniti...
34 篇 cameras

机构

6 篇 hubei key labora...
5 篇 natl inst techno...
5 篇 university of ch...
4 篇 natl inst techno...
4 篇 school of big da...
4 篇 natl inst techno...
4 篇 tongji universit...
4 篇 amrita univ amri...
3 篇 univ chittagong ...
3 篇 csiro ict centre
3 篇 natl. lab. of pa...
3 篇 pattern recognit...
3 篇 university of el...
3 篇 university of an...
3 篇 national laborat...
3 篇 university of mi...
3 篇 universidad esta...
3 篇 birla inst techn...
3 篇 universidad andr...
3 篇 institute of aut...

作者

6 篇 de-shuang huang
5 篇 kang-hyun jo
4 篇 patil nagamma
4 篇 adachi yoshinori
4 篇 sei-ichiro kamat...
4 篇 ma songde
4 篇 donald c. wunsch
4 篇 daniel s. levine
4 篇 anon
4 篇 zhang haitao
4 篇 zhang hao
4 篇 honggang zhang
4 篇 iwahori yuji
3 篇 paul scheunders
3 篇 wilfried philips
3 篇 andersson karl
3 篇 kumar ajay
3 篇 tongwei lu
3 篇 dan popescu
3 篇 soman k. p.

语言

1,814 篇 英文
45 篇 其他
19 篇 中文
1 篇 西班牙文

检索条件"任意字段=4th International Conference on Intelligent Systems and Pattern Recognition-ISPR"

共 1874 条记录，以下是301-310 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：

Tanks detection and recognition based on custom dataset model

Tanks detection and recognition based on custom dataset mode...

引用

Smart Information systems and Technologies (SIST), IEEE international conference on

作者： Vasyl Lytvyn Nazar Oleksiv Mariia Nazarkevych Lviv Polytechnic National University Lviv Ukraine

ISBN: (数字)9798350374865

ISBN: (纸本)9798350374872

this research explores the field of Artificial Intelligence vision, specifically concentrating on training a You Only Look Once (YOLO) model to recognize military objects, with a focus on tanks. Utilizing the capabilities of deep learning and YOLO’s real-time object detection, the study introduces a comprehensive methodology aimed at improving the precision and effectiveness of identifying military assets. the approach encompasses the compilation of diverse datasets, precise annotation, and the development of a customized training plan to equip the YOLO model with the capability to discern intricate features of tanks across various scenarios. through meticulous experimentation and refinement, the trained model demonstrates heightened proficiency in real-world situations, opening avenues for advancements in military surveillance, security, and strategic decision-making. the results underscore the potential of AI vision, particularly YOLO, in fortifying defense systems by enabling intelligent and swift recognition of military objects.

关键词： YOLO Training Surveillance Color Real-time systems Object recognition Time factors

来源：评论

学校读者我要写书评

暂无评论

AI Methods for Personalized Suggestions on Smart Glasses Based on Human Activity recognition

AI Methods for Personalized Suggestions on Smart Glasses Bas...

引用

4th IEEE-EMBS international conference on Wearable and Implantable Body Sensor Networks (BSN) / 18th IEEE-EMBS international conference on Biomedical and Health Informatics (BHI)

作者： Boucharas, Dimitrios G. Androutsos, Christos Tachos, Nikolaos S. Tripoliti, Evanthia E. Manousos, Dimitrios Skaramagkas, Vasileios Ktistakis, Emmanouil Marias, Kostas Tsiknakis, Manolis Fotiadis, Dimitrios I. FORTH Biomed Res Inst Ioannina Greece Univ Ioannina Dept Mat Sci & Engn Unit Med Technol & Intelligent Informat Syst Ioannina Greece FORTH Inst Comp Sci Iraklion Crete Greece Hellen Mediterranean Univ Dept Elect & Comp Engn Iraklion Crete Greece FORTH Dept Biomed Res Ioannina Greece

ISBN: (数字)9781665487917

ISBN: (纸本)9781665487917

Smart wearables are becoming an irreplaceable part of daily living by supporting their users to maintain or adopt healthier lifestyles and monitor their current status. While the trend is increasing, little has been accomplished in the field of personalized solutions. In the present study, two models derived from distinct conceptual themes were developed, and the performance was evaluated utilizing a wearable prototype in the form of smart glasses. A statistical and a reinforcement learning approach were adopted to construct a personalization layer in terms of a predefined system reaction upon specific user behavior. the settings of the present study involve the user behavior derived from Artificial Intelligence (AI) based human activity recognition, among others, and the system reaction being a supportive Augmented Reality (AR) based functionality. Each approach yielding different benefits and drawbacks, imminently leads to a comparative analysis based on the efficiency offered by assessing the inference, update, and trend handling time. Both models are built upon the user's previous data, resulting in a data driven approach that is entirely different for each user and tailored to the user preferences. the results derived from the comparative analysis indicate that both approaches offer the personalization seeked, with the reinforcement learning approach to adapt faster.

关键词： Smart glasses Sensor systems Bayes methods Q-learning

来源：评论

学校读者我要写书评

暂无评论

Research on the Identification Method of GIS Partial Discharge Based on VGG-16 Algorithm

Research on the Identification Method of GIS Partial Dischar...

引用

Energy Engineering and Power systems (EEPS), international conference on

作者： Ziyu Wan Wenbo Huang Fengrui Cheng Xixiu Wu School of Automation Wuhan University of Technology Wuhan China China Power Engineering Consulting Group Central Southern China Electric Power Design Institute co. Wuhan China

ISBN: (数字)9798350366914

ISBN: (纸本)9798350366921

Partial discharge (PD) is one of the important causes of insulation failure in GIS, and it is also an important criterion for evaluating the insulation level of GIS. Accurately identifying the type of GIS PD can effectively assist the relevant operation and maintenance personnel to carry out operation and maintenance of GIS. In order to accurately identify the type of GIS PD, this paper extracts the PRPS pattern of UHF signals from the cloud, summarizes the characteristics of the pattern, and concludes the feasibility of using convolutional neural networks to identify them. then a GIS partial discharge recognition based on VGG-16 is proposed, which takes the GIS pattern directly as the input of the model, and extracts the feature parameter by using the convolutional layer, which avoids the subjectivity in the selection of the feature parameter. the model recognition results show that the model effectively recognizes the GIS PD types, and the accuracy of total PD recognition rate can reach 95.75%

关键词： Partial discharges Insulation Accuracy Predictive models Feature extraction Prediction algorithms Maintenance Power systems Character recognition Personnel

来源：评论

学校读者我要写书评

暂无评论

intelligent fitness system design based on ESP32 and human posture recognition 4

Intelligent fitness system design based on ESP32 and human p...

引用

4th international conference on Robotics, intelligent Control and Artificial Intelligence, RICAI 2022

作者： Chen, Bowen Zhang, Hui Sun, Xuan Duan, Derong School of Mechanical Engineering University of Jinan China

ISBN: (纸本)9781450398343

Aiming at the fixed and single function of fitness device, this system designs an intelligent fitness system that monitors the human body status in real time by the lower computer and judges whether the fitness action is standard by the upper computer. the system uses ESP32 as the main control chip and obtains environmental information and user's body data in real time through temperature and humidity sensor, pH strength sensor and ECG detection sensor. the lower computer uploads the data to the upper computer through UDP communication protocol and visualizes the data. the upper computer connects to the monocular camera and identifies and determines whether the user's fitness movements are standard or not by using the human posture estimation algorithm in deep learning and gives tips. the user performs the exercise according to the prompts. the system ensures the efficiency of fitness and increases the fun of human-computer interaction. © 2022 ACM.

关键词： systems analysis

来源：评论

学校读者我要写书评

暂无评论

Optimization Design of Power Grid intelligent Monitoring System Based on Deep Learning

Optimization Design of Power Grid Intelligent Monitoring Sys...

引用

Electronic Information Engineering and Computer Communication (EIECC), international conference on

作者： Zhixu Hao Shenyang Urban Construction University Shenyang China

ISBN: (数字)9798331534622

ISBN: (纸本)9798331534639

the intelligent monitoring system of the power grid is a critical support for ensuring the safe and stable operation of the grid, and enhancing its intelligence level is of great significance. Addressing issues such as low fault recognition accuracy and slow response speed in traditional monitoring systems, this paper designs an intelligent monitoring system for power grids based on deep learning. A layered architecture is adopted to design the system framework, and a CNN-LSTM hybrid network is constructed for fault diagnosis. Additionally, a distributed data processing platform is built on the Spark framework. Experimental results demonstrate that the proposed system achieves high fault recognition accuracy and data processing capabilities, significantly shortens warning times, reduces deployment and maintenance costs, and provides a feasible technical solution for smart grid development.

关键词： Deep learning Fault diagnosis Adaptation models Accuracy Costs Data processing throughput Smart grids Time factors Monitoring

来源：评论

学校读者我要写书评

暂无评论

Hybrid CNN and Vision Transformer-Based Multi-Factor Authentication for Enhanced Security in Online Examination systems

Hybrid CNN and Vision Transformer-Based Multi-Factor Authent...

引用

Ubiquitous Computing and intelligent Information systems (ICUIS), international conference on

作者： Vallem Ranadheer Reddy Gourishetty Shankar Lingam Peesala Ilanna Amgoth Ashok Kumar Department of Computer Science and Engineering Chaitanya Deemed to be University Kishanpur Hanamkonda Telangana India Department of Computer Science and Engineering Vaagdevi Engineering College Bollikunta Warangal Telangana India

ISBN: (数字)9798331529635

ISBN: (纸本)9798331529642

With the rapid growth of online examination platforms, maintaining high levels of security, integrity, and user authentication is paramount. While existing methods utilize traditional security measures, the integration of advanced deep learning techniques can further improve the robustness of these systems. In this paper, we proposed a hybrid model that combines Convolutional Neural Networks (CNN) and Vision Transformers (ViT) for facial recognition in a multi-factor authentication system for online examinations. the CNN model captures local feature patterns, while the ViT captures the global relationships within the image, by combining these architectures can provide highly effective method for facial recognition tasks. the proposed model use both CNN and ViT in feature extraction and provides robustness. From the experiment results is observed that the proposed model achieves an accuracy of 98%, outperforming conventional methods in the domain of online examination security.

关键词： Measurement Multi-factor authentication Accuracy Face recognition Computational modeling Computer architecture Transformers Robustness Convolutional neural networks Security

来源：评论

学校读者我要写书评

暂无评论

4th international conference on Innovative Computing, IC 2021

4th International Conference on Innovative Computing, IC 202...

引用

4th international conference on Innovative Computing, IC 2021

ISBN: (纸本)9789811642579

the proceedings contain 241 papers. the special focus in this conference is on Innovative Computing. the topics include: Inertial Navigation Method for Spacecraft Based on General Relativity;influencing Mechanism of Live Broadcasting Marketing pattern on Consumers’ Purchase Decision Internet Background;Reinventing the Wheel of Marketing: Assessing the Impact of Artificial Intelligence (AI) on Digital Marketing and Consumer Buying Behavior;Fraud Identification Model of Profit and Loss Adjustment Financial Report Based on Lib SVM Algorithm;stock Price Prediction Based on Deep Reinforcement Learning;space Design of Medical and Maintenance Building Under the Background of Computer;application of Computer Technology in Concrete;design and Implementation of Educational Information System Based on Cloud Computing;Evaluation Model of English–Chinese Cross-Language Initiation Oral Teaching Based on SOFMNN;exploration of Optimized Teaching Mode in Applied Technology Colleges Under the Background of Big Data;efficient-net Speaker recognition Master—the New Speaker recognition System Built Base on Efficient-net;intelligent Invoice Identification Technology Based on Zxing Technology;author Identification of Handwritten Numbers Based on Transfer Learning and Multi-task Learning;influence of Oil Price on Corn Price Based on Multiple Linear Regression Model;An Empirical Analysis of the VAR Model of Consumption Structure, Industrial Structure and Economic Growth in the Internet Age: Taking Henan Province as an Example;a Research on the Influence of Raising the threshold of Individual Income Tax on Urban Residents’ Consumption Based on Eviews Software—A Case Study of Shanghai;effects of Minimum Wage on Enterprise Productivity—Empirical Analysis Based on Database of Industrial Enterprises.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improved Wheat Spike recognition Method Based on YOLOv5 with Added Channel Attention Mechanism

Improved Wheat Spike Recognition Method Based on YOLOv5 with...

引用

Digital Society and intelligent systems (DSInS), international conference on

作者： Li Zhao Zhihong Wang Fang Jia Runfeng Li Lixin Liu Xinyue Zhang Shandong Agriculture and Engineering University Jinan China Shandong Institute of Information Technology Industry Development Jinan China

ISBN: (数字)9798331528829

ISBN: (纸本)9798331528836

Rapid identification and detecting wheat spikes is of great significance for understanding the growth status of wheat, evaluating its growth potential, and estimating future wheat yields. Traditional object detection algorithms often face a trade-off between accuracy and speed. In order to improve the accuracy of wheat spike recognition, this study used an improved one-stage object detection algorithm Yolov5_SE algorithm, which introduced the channel attention mechanism module SE_Block to enhance the focus on local detailed features of wheat spikes and solve the problems of dense and overlapping wheat spikes. this paper continuously changed the position and number of SE_Block in the original network structure when adding the channel attention mechanism to the improved Yolov5 algorithm. the experimental results show that the proposed algorithm in wheat spike recognition tasks achieved better performance, with an average precision (mAP) improvement of 0.8% compared to the original Yolov5 algorithm, while speed was also improved. the results of this study can provide reference and inspiration for the application of machine vision technology in the field of agriculture.

关键词： YOLO Attention mechanisms Accuracy Target recognition Machine vision Face recognition Feature extraction Agriculture intelligent systems Detection algorithms

来源：评论

学校读者我要写书评

暂无评论

Copula Entropy Based Causal Network Discovery from Non-stationary Time Series 27th

Copula Entropy Based Causal Network Discovery from Non-stati...

引用

27th international conference on pattern recognition, ICPR 2024

作者： Yang, Jing Rao, Xinzhi The Intelligent Interconnected Systems Hefei University of Technology Hefei230009 China The School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China

ISBN: (纸本)9783031781827

the task of deducing the causal network from time series data and identifying relationships among multiple series is increasingly vital across various sectors such as industry, medicine, and finance. Despite numerous algorithms being proposed for this purpose, the majority are predicated on the stationarity assumption. However, in disciplines like climatology and neuroscience, time series often exhibit non-stationarity, characterized by a data distribution that shifts over time. In this paper, we introduce an innovative algorithm designed to discern causal relationships from non-stationary time series. Our approach unfolds in three key steps: Initially, we harness the concept of copula entropy to estimate the conditional transfer entropy, offering a streamlined method for non-parametric conditional independence testing. Subsequently, we introduce the time index, which influences other variables at specific time lags, and by integrating the conditional transfer entropy, we execute the independence tests. this leads us to propose the CE-CDN (Copula Entropy-based Causal Discovery from Non-stationary time series), a two-stage algorithm tailored for learning the causal network and identifying change modules. Finally, through comparative analysis with existing algorithms, our experimental findings indicate that CE-CDN not only excels in managing non-stationary time series but also boasts commendable time efficiency. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Time series analysis

来源：评论

学校读者我要写书评

暂无评论

Adaptive Target Detection Algorithm Based On Combining Multimodal Data

Adaptive Target Detection Algorithm Based On Combining Multi...

引用

Energy, Power and Electrical Engineering (EPEE), international conference on

作者： Weichuan Ni Jiajun Zou Zhiping Wan Guangzhou Xinhua University Guangzhou China

ISBN: (数字)9798331518066

ISBN: (纸本)9798331518073

Existing intelligent transport systems suffer from long response times in accident detection and processing, and are unable to provide timely warning and emergency response. To address this challenge, we propose a target behaviour recognition algorithm based on multimodal data understanding. the algorithm aims to improve the data processing and response speed of intelligent transport systems. the algorithm extracts the key information of the target from the multimodal data in the traffic scene. It also introduces an adaptive multi-task learning model combined with an attention mechanism. the mechanism achieves multi-faceted importance scoring of the input information by processing multiple query vectors in parallel. the algorithm automatically adjusts the model focus according to different scores for real-time changes in the traffic scene. the algorithm computes the dot product and weights between the query vectors and the input features, and returns a message for each query that incorporates different modal data and highlights features related to the target behaviour. Based on this information, the algorithm improves the speed and accuracy of target behaviour recognition processing. Experimental results show that the algorithm significantly improves the processing speed and accuracy of target behaviour recognition. It helps to improve the adaptability and responsiveness of the intelligent transport system to complex traffic scenes. For specific data, our algorithm reduces processing time by 0.65 s and improves recognition accuracy by 6% compared to traditional methods.

关键词： Adaptation models Accuracy Attention mechanisms Target recognition Computational modeling Object detection Vectors Real-time systems Time factors Accidents

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188页 << < 27 28 29 30 31 32 33 34 35 36 > >>

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：