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

2,082 篇 会议
9 册 图书
6 篇 期刊文献

馆藏范围

2,097 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

1,348 篇 工学
- 1,052 篇 计算机科学与技术...
- 861 篇 软件工程
- 476 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...
- 67 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...
25 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

2,034 篇 英文
63 篇 其他
11 篇 中文

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

共 2097 条记录，以下是241-250 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：

Detect Alzheimer's Disease from Neuroimaging Using Artificial intelligence Techniques 3

Detect Alzheimer's Disease from Neuroimaging Using Artificia...

引用

3rd international conference on Computing and Information technology, ICCIT 2023

作者： Alarjani, Maitha King Faisal University College of Computer Science and Information Technology Department of Computer Sciences Al Hofuf36362 Saudi Arabia

ISBN: (纸本)9798350321487

Alzheimer's disease (AD) is the continuous deterioration of cognitive, behavioral, and social skills that affects a person's ability to function independently. It is the most common cause of memory impairment and dementia. Early detection is considered one of the most important factors that helps make plans and prevent the development of symptoms of this disease. The purpose of this work is to compare machine learning (ML) and deep learning (DL) models to detect early warning signs of AD. In addition, a neural network is utilized to extract important features and distinguish between healthy brain imaging and that of those affected by mild cognitive impairment (MCI). A 3D convolutional neural network (3D-CNN) architecture is utilized to compute the features of neuroimaging data. After that, the feature vector is fed to the support vector machines (SVM) for final recognition. The system is assessed using a publicly available ADNI dataset for functional magnetic resonance imaging (fMRI). In the case of a 3D convolutional neural network, a recognition rate of 98.92% and 98.3% is attained on training and testing, respectively. In the case of the SVM model, an accuracy of 97.14% and 97.5% is achieved on training and testing, respectively. © 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

Optimal Dispatching of of Wind Power Hydrogen Production system 3

Optimal Dispatching of of Wind Power Hydrogen Production Sys...

引用

3rd international conference on New Energy and Power Engineering, ICNEPE 2023

作者： Yao, Fulai Yao, Yaming Zhanga, Shengyong Hebei University of Technology School of Artificial Intelligence Tianjin China Beijing Iao Technology Development Company Department of Technology Beijing China

ISBN: (纸本)9798350393224

This article presents a simple method to achieve energy efficiency optimization without establishing an accurate mathematical model of the hydrogen production station. The optimal load distribution method between hydrogen generators is proved, that is, keeping the operating energy efficiency of each operating electrolyser equal, that is, Yao's theorem 1. It was also proved that the optimal switching method of the number of operating units between hydrogen generators is to keep the switching at the same point of the overall energy efficiency of the hydrogen production station, or the maximum capacity point of the hydrogen generator, that is, Yao's Theorem 2. © 2023 IEEE.

关键词： energy efficiency hydrogen production optimization wind power

来源：评论

学校读者我要写书评

暂无评论

BFNet: Brain-like Feedback Network for Object detection under Severe Weather 3

BFNet: Brain-like Feedback Network for Object Detection unde...

引用

3rd IEEE international conference on Digital Twins and Parallel intelligence, DTPI 2023

作者： Fan, Lili Zeng, Changxian Li, Yunjie Gao, Ruiyang Liu, Jianjian Cao, Dongpu Beijing Institute of Technology School of Information and Electronics Beijing China Dalian Minzu University School of Science Dalian China Beijing University of Posts and Telecommunications International School Beijing China Byd Auto Industry Company Limited Auto Engineering Research Institute Shenzhen China Tsinghua University School of Vehicle and Mobility Beijing China

ISBN: (纸本)9798350318470

Despite the demonstrated promising results achieved by deep learning-based object detection methods on conventional datasets, the object detection presents a significantly greater challenge when confronted with poor perception captured under adverse weather. Existing methods are studying how to improve the ability of the model to extract features by reducing the impact of severe weather on images, but these methods contradict the human visual cognition process. Based on the mechanism of visual cognition, we propose a novel object detection model based on brain-like feedback, which improves the detection performance of the model and has strong interpret ability. Specifically, an initial environment cognition assessment method is proposed, which is used to evaluate high-level prior knowledge and improve the ability to process and integrate low-level information;In addition, the amodal predictive completion method is proposed, which solves the problem of object blur and uncertainty caused by limited visual perception, and realizes the shape prediction of unknown objects. The experimental results are surprising, demonstrating the effectiveness of our method in severe weather. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Artificial intelligence and Supervised Learning based Solid Waste Segregation Mechanism using ESP 32 3

Artificial Intelligence and Supervised Learning based Solid ...

引用

3rd international conference on Ubiquitous Computing and Intelligent Information systems, ICUIS 2023

作者： Srinevasan, M. Parameshwari, V. Abirami, T. Divyaa, N. Nandha Engineering College Dept of Ece Erode India M. Kumarasamy College of Engineering Dept of Ece Karur India Velalar College of Engineering and Technology Dept of Ece Erode India

ISBN: (纸本)9798350306989

Garbage separation must take place at the household level because it is time-consuming and frequently unsuccessful to do it at the disposal. This Proposed method attempts to decrease mannual effort in segregation of waste in order to achieve proper waste segregation with the least amount of effort. This proposed system suggests an automatic trash segregator system powered by IOT. In addition to detecting and classifying household rubbish into dry, moist, and metallic waste streams, it aids in real-time monitoring the levels of garbage in trash discharges. A metallic sensor is then used to determine whether there is any metal in the garbage after an Ultrosonic [radar based] has detected the arrival of the trash. Additionally, the trash is separated using the capacitive detector into dry and moist residue. The conveyor helps to move the waste to the proper bins before the platform rotates once it has been detected and segregated using a supervised learning-based algorithm. Additionally, the system uses ESP 32 to display a note to clean the trash can when it is occupied and to show the amount of compost in the trash discharges on the LCD screen. Experimental results show that the proposed method is effective in categorizing waste into moist and dry waste as well as metal and non-metal waste. © 2023 IEEE.

关键词： Supervised learning

来源：评论

学校读者我要写书评

暂无评论

3rd international conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2023

3rd International Conference on Evolutionary Computing and M...

引用

3rd international conference on Evolutionary Computing and Mobile Sustainable Networks, ICECMSN 2023

The proceedings contain 96 papers. The topics discussed include: development of renewable energy system for enhancing reliability of power;leveraging the power of blockchain technology for building a resilient crowdfunding solution;an evolutionary fuzzy system for multiclustering in data streaming;decentralized and multi-authority based public key infrastructure for sharing electronic health records;a novel edge-aware image fusion approach for thermal and visible images;AI-enhanced defect identification in construction quality prediction: hybrid model of unsupervised and supervised machine learning;phishing detection using gradient boosting classifier;leveraging machine learning for customer intelligence: an experimental analysis learning classifiers;and optimizing wireless sensor network routing through memetic algorithms: enhancing energy efficiency and data reliability.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Intelligent phase detection of signals on varying SNR using machine learning algorithms 3

Intelligent phase detection of signals on varying SNR using ...

引用

3rd international conference on Range technology, ICORT 2023

作者： Halder, Somnath Sonar, Souvik National Institute of Technology Odisha Rourkela India Integrated Test Range DRDO Odisha Chandipur India

ISBN: (纸本)9781665493314

The phase detection as a part of phased-locked loop (PLL) circuit is a critical component in any telecommunication systems. With the advancement of modern-era technologies, the researchers are trying to replace the complicated hardware circuitry with the machine learning algorithms with high degree of accuracy thereby making the system more compact. This paper introduces efficient techniques for machine learning (ML) classifiers that are able to classify a time-domain input signal for the accurate detection of phase shift *** a reference signal. The incoming input signal is synchronised with the reference signal by using a pseudo-random pilot sequence present in the signal itself. The proposed schemes replicate the phase detection circuit with ML based software model without compromising the efficacy in terms of the receiving system functionality. The ML model designed is able to detect the phase of an incoming signal upto 93% accuracy in Additive white Gaussian noise (AWGN) channel. © 2023 IEEE.

关键词： Gaussian noise (electronic)

来源：评论

学校读者我要写书评

暂无评论

Research Status, Hotspots and Trends of international AI-assisted Second Language Learning 6

Research Status, Hotspots and Trends of International AI-ass...

引用

6th international conference on Educational technology Management (ICETM)

作者： Li, Yuxin Chen, Rui Wu, Juan Beijing Normal Univ Fac Educ Sch Educ Technol 19 XinJieKouWai St Beijing Peoples R China Beijing Normal Univ Adv Innovat Ctr Future Educ Beishahe West 3rd Rd Beijing Peoples R China

ISBN: (纸本)9798400716676

The widespread application of artificial intelligence has triggered important changes in second language learning. The study was conducted on 293 research articles cited in the Web of Science database from 2013 to 2022 using the Bibliometrix R-package and CiteSpace software. A comprehensive investigation and analysis in the field of international artificial intelligence-assisted second language learning in the past ten years was made in this study, specifically including the development trend, high-cited authors, high-yield regions, high-impact journals, core article topics and research hot topics. The study found that (1) the overall research in this field shows a booming trend;(2) the field has formed highly influential authors and countries and has formed a relatively concentrated core journal group;and (3) the core article topics focus on combination of corpus linguistics and computational linguistics. The research hotspots include the creation of second language learning situations, the development of multilingual skills, the accurate assessment and diagnosis of second language learning, and the automatic feedback system for second language learning. Based on the analysis of the research results, this paper sorts out the future research trends in this field, and provides reference and inspiration for the research and practice of second language learning.

关键词： Artificial intelligence Second language learning Artificial intelligence-assisted language learning Bibliometric analysis Visual analysis

来源：评论

学校读者我要写书评

暂无评论

Wi-Move: Moving Object detection Based on Fresnel Zone Model 3

Wi-Move: Moving Object Detection Based on Fresnel Zone Model

引用

3rd international conference on Computer Science, Electronic Information Engineering and Intelligent Control technology, CEI 2023

作者： Ge, Benling Fu, Xianxin Peng, Min Hefei University of Technology Hefei China

ISBN: (纸本)9798350372052

Detecting moving objects is crucial in security, but current motion detectors are bulky and costly, limiting widespread deployment. In this paper, according to the Fresnel zone model and the difference in reflective power of different objects, the feasibility of detecting moving objects is proved theoretically, and a moving object detection system based on Channel State Information (CSI) is designed. The system proposes a threshold-based sliding variance and waveform truncation method to extract the object motion segment. A hybrid model utilizing Convolutional Neural Networks (CNN) and Long Short Term Memory (LSTM) as the feature extraction layer and Support Vector Machine (SVM) as the classification layer is constructed. We carried objects at a constant speed by moving the slide and conducted numerous experiments with eight common types of objects. The experimental results demonstrate that the average accuracy of Wi-Move is 96.01% in 1m detection distance and can effectively recognize moving objects. © 2023 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Malpractice detection in Online Proctoring using Deep Learning 3

Malpractice Detection in Online Proctoring using Deep Learni...

引用

3rd international conference on Artificial intelligence and Smart Energy, ICAIS 2023

作者： Raga Priya, Immadi Dhatri Sree Ramya, Ponnaluri Vamshi, Mulugu Veera Chandana, Bhimavarapu Rao, M.Kameswara Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Vaddeswaram India

ISBN: (纸本)9781665462167

One of the most effective image processing applications, face recognition is crucial in the technical world. An ongoing problem with authentication is the ability to recognize a person's face, particularly when it comes to tracking students' movements in an examination. It is a pupil identification method that employs face biostatistics based on multiple technologies. The creation of this system aims to digitally replace physical invigilation with the digital view. The manual recording makes it harder to concentrate on numerous students. HOG classifiers, CNN, SVM, Generative Adversarial Networks, and Gabor filters are used in the suggested system. Face detection systems have grown over years and the industry has paid close attention to this topic. Numerous studies have been conducted on face and eye identification. Reports will be generated and saved following face recognition. The system is tested under different conditions, which include head movements, and changing distances between the person and the cameras. Overall accuracy is determined after testing. This system is efficient to reduce malpractice in less time. The created system is inexpensive and requires little installation. © 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

A New Approach for Leaf Disease detection using Multilayered Convolutional Neural Network 3

A New Approach for Leaf Disease Detection using Multilayered...

引用

3rd international conference on Artificial intelligence and Signal Processing, AISP 2023

作者： Shukla, Vivek Rani, Sweta Mohapatra, Ramesh Kumar National Institute of Technology Department of Computer Science Odisha Rourkela India

ISBN: (纸本)9798350320749

Leaf diseases reduce agricultural yield by 35% annually in India, where agriculture is the main sector. Manual detection of the type of disease present in leaves takes a long time since laboratories lack the necessary tools and expertise to recognise early leaf diseases. Diseases include early blight, late blight, black root, bacterial spot, mould leaf, healthy leaf, etc. Automated leaf disease detection systems are beneficial for spotting disease symptoms on plant leaves as soon as they appear, which helps to ease the time-consuming process of monitoring large agricultural farms. Recent advances in deep learning (DL) and computer vision models have highlighted the importance of developing autonomous leaf disease detection algorithms based on visual symptoms on leaves. The fundamental goal of the proposed model is to tackle the problem of leaf disease diagnosis using the most basic strategy while utilising the fewest computer resources to generate results comparable to state-of-the-art techniques. We used the multilayered architecture of convolutional neural networks (CNN) to identify and overcome leaf diseases. When compared to existing techniques, our proposed method can successfully train an image classification model to achieve 98.5% accuracy. © 2023 IEEE.

关键词： Convolutional neural networks

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210页 << < 21 22 23 24 25 26 27 28 29 30 > >>

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：