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

2,086 篇 会议
9 册 图书
6 篇 期刊文献

馆藏范围

2,101 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,352 篇 工学
- 1,054 篇 计算机科学与技术...
- 863 篇 软件工程
- 478 篇 信息与通信工程
- 293 篇 控制科学与工程
- 282 篇 生物工程
- 210 篇 电气工程
- 155 篇 网络空间安全
- 141 篇 光学工程
- 139 篇 生物医学工程（可授...
- 133 篇 电子科学与技术（可...
- 126 篇 仪器科学与技术
- 126 篇 安全科学与工程
- 91 篇 机械工程
- 85 篇 化学工程与技术
- 81 篇 动力工程及工程热...
- 74 篇 材料科学与工程（可...
- 68 篇 交通运输工程
764 篇 理学
- 325 篇 数学
- 298 篇 生物学
- 194 篇 物理学
- 143 篇 化学
- 106 篇 统计学（可授理学、...
355 篇 管理学
- 222 篇 管理科学与工程(可...
- 155 篇 图书情报与档案管...
- 89 篇 工商管理
153 篇 医学
- 128 篇 临床医学
- 126 篇 基础医学(可授医学...
- 84 篇 药学(可授医学、理...
- 77 篇 公共卫生与预防医...
71 篇 法学
- 60 篇 社会学
42 篇 农学
36 篇 经济学
23 篇 教育学
6 篇 军事学
1 篇 文学

主题

94 篇 object detection
70 篇 artificial intel...
52 篇 deep learning
48 篇 machine learning
41 篇 internet of thin...
37 篇 feature extracti...
30 篇 intrusion detect...
26 篇 support vector m...
25 篇 anomaly detectio...
25 篇 fault detection
24 篇 face recognition
24 篇 computer vision
21 篇 convolutional ne...
16 篇 convolution
14 篇 image processing
13 篇 real-time system...
12 篇 covid-19
12 篇 network security
12 篇 diseases
10 篇 cameras

机构

38 篇 maharishi school...
34 篇 national univers...
32 篇 the islamic univ...
31 篇 school of comput...
30 篇 uttaranchal inst...
29 篇 chitkara univers...
28 篇 centre of interd...
26 篇 lovely professio...
26 篇 department of ar...
21 篇 uttaranchal univ...
20 篇 vishwakarma inst...
19 篇 college of intel...
18 篇 sr university sc...
16 篇 college of pharm...
15 篇 department of co...
13 篇 school of comput...
13 篇 school of comput...
12 篇 school of comput...
11 篇 school of comput...
11 篇 department of el...

作者

12 篇 rajesh singh
11 篇 singh rajesh
10 篇 malik bader alaz...
8 篇 mohit tiwari
7 篇 yifeng niu
7 篇 kapil joshi
7 篇 wenxing fu
7 篇 gehlot anita
7 篇 mancang gu
7 篇 alazzam malik ba...
7 篇 kumar bura vijay
7 篇 yi qu
7 篇 tiwari mohit
7 篇 anita gehlot
6 篇 alfurhood badria...
6 篇 joshi kapil
6 篇 malik praveen ku...
6 篇 bura vijay kumar
6 篇 chauhan rahul
6 篇 badria sulaiman ...

语言

2,011 篇 英文
90 篇 其他
14 篇 中文

检索条件"任意字段=2023 3rd International Conference on Detection Technology and Intelligence System, DTIS 2023"

共 2101 条记录，以下是641-650 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 Industrial Internet Cloud Platform system Based on Layout Application 3

Design of Industrial Internet Cloud Platform System Based on...

引用

3rd Guangdong-Hong Kong-Macao Greater Bay Area Artificial intelligence and Big Data Forum, AIBDF 2023

作者： Ji, Jun Cui, Jian Cheng, Guanhong Beijing Polytechnic Beijing China

ISBN: (纸本)9798400716362

The industrial internet supports the development of the digital economy. This article is based on the industrial layout application field and adopts the industrial internet private cloud platform to build a system functional architecture and technical architecture, achieving the functions of on-site control system module, information collection module, layout optimization algorithm module, and intrusion detection module. This paper first investigates the application situation in the field of industrial layout applications, finds effective cloud platform design solutions, and then verifies the feasibility of the solutions through commonly used enterprise cases. © 2023 Copyright held by the owner/author(s).

关键词： Intrusion detection

来源：评论

学校读者我要写书评

暂无评论

Designing a Deep Learning Model for recommendation of Drugs on Sentiment Analysis 3

Designing a Deep Learning Model for recommendation of Drugs ...

引用

3rd IEEE Mysore Sub Section international conference, MysuruCon 2023

作者： Aruna, T.M. Nethravathi, T.L. Muniraju, M. Nitte Meenakshi Institute of Technology Dept of AI-ML Bengaluru India SJCIT Chickballapur Department of Artificial Intelligence and Machine Learning 562101 India

ISBN: (纸本)9798350340358

There has been a rise in creative automation work in recent years, and various applications have been found for machine learning. This essay's focus is on introducing a pharmaceutical recommendation system with the potential to greatly reduce the burden on experts. With the help of a deep learning algorithm, we create a drug recommendation system that utilises patient reviews to predict sentiment through the use of a number of vectorization techniques. Synthetic minority over-sampling method (SMOTE) is used to rectify the effects of unbalanced data on classification accuracy. The evaluation is sorted using a Recurrent Neural Network (RNN), with the weights chosen using an enhanced version of the firefly optimisation algorithm (IFFOA). Predicted feelings were evaluated using a battery of metrics counting precision, recall, f1score, accuracy, and specificity score. The classifier RNN-FCR has a higher accuracy rate (96%) than any other models as a direct result of TF-IDF vectorization. © 2023 IEEE.

关键词： Recurrent neural networks

来源：评论

学校读者我要写书评

暂无评论

Dental X-Ray Image Analysis for Diagnosis Utilized Convolutional Neural Network Using Real-Time Performance 3

Dental X-Ray Image Analysis for Diagnosis Utilized Convoluti...

引用

3rd IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2023

作者： Arabi, Mohammed Yousif Ramadan, Ghazi Mohamad Reddy, R Archana Habelalmateen, Mohammed I. Priyanka, K. National University of Science and Technology Dhi Qar Iraq College of MLT Ahl Al Bayt University Karbala Iraq School of Computer Science and Artificial Intelligence SR University Telangana Warangal India The Islamic University Najaf Iraq Nitte Meenakshi Institute of Technology Department of Information Science and Engineering Bengaluru India

ISBN: (纸本)9798350317022

The diagnostic methods available to dentists for caries detection have multiplied in dental X-ray images. In the research, a classification system was designed using Convolutional Neural Network (CNN) analysis to obtain the best parameters for the system. CNNs can be trained to detect and classify dental conditions, such as cavities which can assist dentists in diagnosing and treatment planning. The large number of X-ray images allows dentists to make quicker decisions, reducing the time and risk of interpreting the X-rays. After testing three different image sizes, it was found that an image size of 224 × 224 pixels yielded the best testing results and graphs. This is because each pixel contains information about the image, and larger image sizes provide more detailed information. Therefore, over time, monitoring with CNNs can help dentists track the progress of ongoing treatments and interventions. To evaluate the effectiveness of these models, experiments were conducted on a manually annotated dataset known as Dental X-ray Images. The experimental results demonstrate that the CNN achieved an accuracy rate of 98.60%, surpassing other existing models such as ResNet, U-Net, and DenseNet. © 2023 IEEE.

关键词： Convolutional Neural Network Dental X-Ray Image Histogram Equalization ResNet and U-Net

来源：评论

学校读者我要写书评

暂无评论

Suspicious Object Tracking With Yolov3 with Python Using Open-CV 3

Suspicious Object Tracking With Yolov3 with Python Using Ope...

引用

3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Gautam, Deepanshu Gupta, Harsh Shekhar, Himanshu Kumar, Manish Nasser, Sarmad Jaafar Fouad, Laith Galgotias College of Engineering and Technology Dept. of Electrical and Electronics Engineering Greater Noida India National University of Science and Technology Collage of Engineering Dhi Qar Iraq Al-Farahidi University Medical Laboratory Techniques Department Baghdad Iraq

ISBN: (纸本)9798350399264

Object tracking system is essential for the surveillance of the suspicious abandoned objects. Tracking of the suspicious abandoned object is widely used in many areas such as airports, railway station and on its track, parking lots and public transportations to prevent terrorism and avoid the incident related to it. Precise recognition of the abandoned objects in an image arena can detect many applications using different vision algorithms. In this research paper, we present a multi-object tracking model along with left over baggage detection in a real time environment. In this article, we present the analysis of track-by-track methods, including the YOLO track and the SORT algorithm track. This article contains details about a procedure dataset of image edify with YOLO for 6 specific category, which is cumulated in videos for detection by the SORT algorithm. Identifying vehicles or pedestrians in continuous videos is useful for congestion survey. The purpose of this article is to analyze and understand the province. © 2023 IEEE.

关键词： Traffic congestion

来源：评论

学校读者我要写书评

暂无评论

A Novel PCB Defect detection Method Based on Digital Image Processing 3

A Novel PCB Defect Detection Method Based on Digital Image P...

引用

2023 3rd international conference on Artificial intelligence and Industrial technology Applications, AIITA 2023

作者： Zhang, Guangxin Cao, Yu Liaoning Petrochemical University School of Information and Control Engineering Liaoning Fushun113001 China

Printed circuit board (PCB) has a wide range of applications, and its automated quality inspection is a vital part of economic production. The time overhead of the current PCB defect detection method will increase with the increase in the number of detection targets. To ensure the stability of detection performance, this paper proposes a novel PCB detection method based on color threshold segmentation. Experiments show that this method can effectively detect and analyse various information about solder pads and solder pastes, among which the detection accuracy rate of solder pads is 99.4%, the missed detection rate is 0.4%, and the detection accuracy rate of solder paste is 99.3%, The missed detection rate is 0.03%. At the same time, the method in this paper has better robustness and stability than other PCB defect detection methods, and can better meet the needs of industrial production. © Published under licence by IOP Publishing Ltd.

关键词： Printed circuit boards

来源：评论

学校读者我要写书评

暂无评论

Multi-class multi-object detection and tracking system in 3 dimensions using YOLOv5 3

Multi-class multi-object detection and tracking system in 3 ...

引用

3rd international conference on Range technology, ICORT 2023

作者： Bhateja, Aditi Sharma, Sanyam Krishna, Abhishek Chaudhary, Himanshu Lall, Brejesh Kalra, Prem K Computer Science Indian Institute of Technology Delhi India Delhi Technological University Software Engineering Delhi India Delhi Technological University Information Technology Delhi India Securities and Exchange Board of India India Electrical Engineering Indian Institute of Technology Delhi India

ISBN: (纸本)9781665493314

It is of great significance to detect and track multiple objects belonging to multiple classes in 3 dimensions and the same can be applied to various research domains. One such application pertains to multi-fish detection and tracking The problem is of significance to marine researchers who want to study the behaviour of fish in a constrained environment i.e. in an aquarium, using different sensors. For this study, a data set consisting of different fishes in an aquarium was constructed and Microsoft Kinect was used to capture the movements in 3 dimensions. The data set was cleaned, aligned, and calibration was done to make it suitable for object detection and tracking In this paper, YOLOv5s model was improvised, hereafter referred as YOLOv5-With Attention Mechanism (YOLOv5-WAM), and an object detection and tracking pipeline was designed to detect and track underwater objects (fishes in our work) belonging to multiple classes in 3D. YOLOv5-WAM can be adapted for use on devices having low compute availability, making it suitable for real time object detection and tracking using low cost experimental setup. YOLOv5-WAM showed about 1% improvement in mAP for our custom dataset while for Fish4Knowkdge and COCO dataset, the improvements were to the tune of 7% when compared to YOLOv5s. The results and analysis of the approach are presented in this paper. © 2023 IEEE.

关键词： Fish

来源：评论

学校读者我要写书评

暂无评论

EAFNet: Feature Enhancement and Self-Adaptive Guided Feature Fusion for Object detection in Haze Conditions 3

EAFNet: Feature Enhancement and Self-Adaptive Guided Feature...

引用

3rd international conference on Electronic Information Engineering and Computer, EIECT 2023

作者： Hu, Xinxin Zhou, Yuanbo Kuang, Xu Chen, Hao Lin, Xiaoyong Liu, Fang Liu, Hongjun Wang, Xiaofei Tong, Tong Gao, Qinquan Fuzhou University Fuzhou China Xiamen University of Technology Fujian Provincial Key Laboratory for Network Audiovisual Application Innovationand Fujian China Chongqing Dadukou District Archives Chongqing China Imperial Vision Technology FuzhouFujian China

ISBN: (纸本)9798350357707

Recently, there is a significant success in the current object detection task. However, existing research has demonstrated that detectors trained on regular images experience a significant decrease when facing to wild scences such as haze scence. Although enhancing detection performance is possible through multi-stage adaptive parameter-guided image enhancement, this method fails to consistently enhance downstream object detection performance. To address this issue, we propose an end-To-end object detection framework that utilizes weakly supervised parameter-guided feature fusion to improve detection performance. Specifically, we introduce the Self-Adaptive Feature Fusion Module (SAFFM) that dynamically guides feature fusion in the detection network through the haze image information encoded by the Prior Knowledge (PK) components. By the joint learning of the PK components and the detection network in an end-To-end manner, we ensure that the PK components weakly supervise the feature fusion process to enhance detection performance. Additionally, we propose a Downsampling Feature Enhancement Module (DFEM) that utilizes multibranch down-sampling operators and reparameterization to enhance the feature extraction capability of the network, allowing it to capture more latent information. Comprehensive experiments on synthetic datasets and real datasets, demonstrated that the detection performance of the proposed network significantly outperforms other state-of-The-Art detection methods. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Data Mining and AI Approaches for Early detection and Management of Gastrointestinal Disorders 3

Data Mining and AI Approaches for Early Detection and Manage...

引用

3rd IEEE international conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Natrayan, L. Ali, H. Mohammed Kaliappan, S. Kumar, Bura Vijay Saveetha School of Engineering Simats Dept. of Mechanical Engineering TN Chennai India Srm Institute of Science and Technology- Ramapuram Dept. of Mechanical Engineering TN Chennai India Lovely Professional University Division of Research and Development Punjab Phagwara India School of Computer Science and Artificial Intelligence Sr University Telangana Warangal India

ISBN: (纸本)9798350343274

This study presents an innovative integration of Data Mining and Artificial intelligence (AI) to advance early detection and management of gastrointestinal disorders. The methodology encompasses data preprocessing, feature selection, model development, and continuous monitoring for timely intervention. Preprocessing involves standardization and normalization to ensure consistent feature scaling and distribution. Addressing missing values and outliers is achieved using suitable methods such as mean imputation and robust statistical techniques. Feature selection methods, including Recursive Feature Elimination (RFE) and Principal Component Analysis (PCA), aid in identifying the most informative features associated with gastrointestinal disorders. Support Vector Machines (SVM) excels in binary classification, distinguishing healthy individuals from those with gastrointestinal disorders. Deep Neural Network (DNN) is employed for non-linear feature representation and classification. In conclusion, the proposed method showcased superior performance in critical parameters when compared to traditional methodologies. Its enhanced accuracy, sensitivity, specificity, and computational efficiency position it as a promising approach in the domain of Data Mining and AI for early detection and management of gastrointestinal disorders. This innovation holds potential for significant advancements, promising improved healthcare outcomes and better lives for individuals suffering from gastrointestinal disorders. © 2023 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Implementation of a smart parking system using LoRa, STM32 Board & IoT 3

Implementation of a smart parking system using LoRa, STM32 B...

引用

3rd international conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Malik, Praveen Kumar Malik, Arun Sunil, G. Naim, Arshi Sharma, Ram Kumar Kathuria, Samta School of Electronics and Electrical Engineering Lovely Professional University Punjab Jalandhar India School of Computer Science and Engineering Lovely Professional University Punjab Jalandhar India School of Computer Science & Artificial Intelligence Sr University Warangal India King Khalid University Department of Business Management Aseer AlSamer University campus Abha Saudi Arabia Raj Kumar Goel Institute of Technology Uttar Pradesh Ghaziabad India Law College of Dehradun Uttaranchal University Dehradun India

ISBN: (纸本)9798350330724

A parking system with technology is an automated system that makes better use of cutting-edge technology to manage parking spaces. These systems typically monitor the occupancy of parking spaces and advise vehicles in real-time about the availability of parking spaces by combining sensors, wireless communication technologies, and software algorithms. In this project, the use of an STM32 board and Long Range (LoRa) communication technology to automate a parking system over the Internet is suggested. Smart parking systems can communicate over great distances with less power usage thanks to the use of LoRa technology. The system is made to be economical and effective, offering a workable answer to the issue of parking in congested region. The project shows that a smart parking system can be implemented using LoRa and an STM32 board and may be further improved by adding features like automated payment methods and parking space reservations. The technology is built to give consumers access to real-time information regarding parking spot availability via a mobile app. The research shows that a cost-effective and practical smart parking system may be implemented utilizing LoRa and an STM32 board. © 2023 IEEE.

关键词： Wireless sensor networks

来源：评论

学校读者我要写书评

暂无评论

Evaluation method of singing pronunciation quality based on artificial intelligence technology 3

Evaluation method of singing pronunciation quality based on ...

引用

3rd international conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT2023

作者： Tang, Hanzhang Southwest University of Science and Technology Mianyang621010 China

Since people have limited ability to judge the quality of their own singing and pronunciation, it is difficult to find problems on their own after reaching a certain level, so they need external help. However, external help also comes from human beings in the past and has many limitations. Therefore, in order to provide better help, this paper will carry out research from the perspective of artificial intelligence. In this paper, the basic concepts of artificial intelligence technology are discussed, and then the evaluation ideas of singing pronunciation quality on the technical level are put forward. Finally, the method system is designed. © 2023 The Authors. Published by Elsevier B.V.

关键词： Quality control

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211页 << < 61 62 63 64 65 66 67 68 69 70 > >>

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：