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

771 篇 会议
5 册 图书
1 篇 期刊文献

馆藏范围

777 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

462 篇 工学
- 401 篇 计算机科学与技术...
- 230 篇 软件工程
- 134 篇 信息与通信工程
- 107 篇 电气工程
- 60 篇 生物医学工程（可授...
- 58 篇 生物工程
- 37 篇 控制科学与工程
- 33 篇 电子科学与技术（可...
- 20 篇 光学工程
- 15 篇 化学工程与技术
- 14 篇 仪器科学与技术
- 13 篇 机械工程
- 12 篇 安全科学与工程
- 11 篇 动力工程及工程热...
- 10 篇 交通运输工程
173 篇 理学
- 91 篇 数学
- 65 篇 生物学
- 43 篇 物理学
- 37 篇 统计学（可授理学、...
- 28 篇 系统科学
- 15 篇 化学
97 篇 管理学
- 63 篇 图书情报与档案管...
- 38 篇 管理科学与工程(可...
- 23 篇 工商管理
63 篇 医学
- 54 篇 临床医学
- 40 篇 基础医学(可授医学...
- 31 篇 药学(可授医学、理...
13 篇 法学
- 12 篇 社会学
13 篇 农学
- 13 篇 作物学
12 篇 教育学
- 12 篇 教育学
8 篇 经济学
1 篇 军事学

主题

207 篇 machine learning
93 篇 signal processin...
87 篇 deep learning
64 篇 signal processin...
62 篇 feature extracti...
56 篇 support vector m...
50 篇 training
49 篇 machine learning...
30 篇 neural networks
21 篇 natural language...
20 篇 image processing
16 篇 computational mo...
14 篇 prediction algor...
13 篇 svm
13 篇 sentiment analys...
13 篇 data models
12 篇 internet of thin...
12 篇 estimation
12 篇 convolutional ne...
11 篇 covid-19

机构

6 篇 college of engin...
6 篇 department of co...
4 篇 xidian universit...
3 篇 department of el...
3 篇 university of du...
3 篇 peng cheng labor...
3 篇 uttaranchal inst...
3 篇 department of el...
3 篇 national laborat...
3 篇 graphic era deem...
2 篇 kl business scho...
2 篇 khulna universit...
2 篇 khulna universit...
2 篇 northwest minzu ...
2 篇 shandong univers...
2 篇 central universi...
2 篇 imt cdl ghaziaba...
2 篇 department of co...
2 篇 school of marine...
2 篇 school of comput...

作者

8 篇 wathiq mansoor
4 篇 yassine himeur
3 篇 alavikunhu panth...
3 篇 li zheng
3 篇 abigail copiaco
3 篇 jing wang
3 篇 joel alanya-belt...
3 篇 rashid ali
3 篇 shadi atalla
3 篇 abbes amira
3 篇 lei huang
2 篇 cheng xinzhou
2 篇 sherin m. yousse...
2 篇 liashchynskyi pe...
2 篇 kumar ashwani
2 篇 sarno riyanarto
2 篇 khawla a. alnajj...
2 篇 chang ming-ching
2 篇 liu ze-guo
2 篇 taleb mohammed

语言

761 篇 英文
13 篇 其他
2 篇 西班牙文
2 篇 中文

检索条件"任意字段=5th International Conference on Signal Processing and Machine Learning, SPML 2022"

共 777 条记录，以下是271-280 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：

An Experimental Investigation on the Emotion Recognition Using Power Spectrum Density and machine learning Algorithms in EEG signals 5th

An Experimental Investigation on the Emotion Recognition Usi...

引用

5th EAI international conference on Big Data Innovation for Sustainable Cognitive Computing, BDCC 2022

作者： Babu, Nirmal Varghese Kanaga, E. Grace Mary Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Tamil Nadu Coimbatore India

ISBN: (纸本)9783031283239

Emotion recognition is a technique for identifying and classifying human emotions by combining biosensing, face recognition, speech and voice recognition, machine learning, and pattern recognition. the electroencephalogram (EEG), which is based on brain signals, is used in the proposed work to identify the emotions. Here, the DEAP dataset is used to gather information about human emotional states, and machine learning algorithms like SVM, KNN, and MLP were used as the classifiers. In this proposed work, we used Power Spectrum Density as the Feature Extraction Technique and Welch’s Periodogram as the signal Decomposition Technique. It was observed that gamma signals show more Valence, whereas Alpha signals show Arousal. To Cross validation system has been used to validate the performance of classifiers used in the work. Based on the locations of the electrode, EEG bands, and classifiers, accuracy comparisons were done. Out of the three classifiers, KNN scored more accuracy than other classifiers used. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

2022 8th international conference on signal processing and Communication, ICSC 2022

2022 8th International Conference on Signal Processing and C...

引用

8th international conference on signal processing and Communication, ICSC 2022

ISBN: (纸本)9781665454308

the proceedings contain 121 papers. the topics discussed include: a study on anomaly detection with deep learning models for IoT time series sensor data;a study on machine learning algorithms for lung cancer classification and prediction;an effective approach to speech-based email assistance for visually impaired people;an efficient polynomial based quantum key distribution approach for secure communication;an investigation on smart crop protection system utilizing internet of things;analyzing influential impact of online trends on social media channels;channel estimation of 5G new radio using convolutional neural network;clustering based intelligent spectrum sensing in cognitive radio network;compact dualband bandstop filter on liquid crystal polymer;design and simulation of RF MEMS switch using uniform serpentine flexure four meander type beam;different dielectric material used for flexible antenna: a review;easy mandi - an agricultural production trading platform for Indian markets;and four-stages stepped-impedance resonator based ultra-wideband bandpass filter with tunable notches.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Comparison of the Performance of Forward-Looking Imaging Systems: Phased-Array or MIMO Radar 5

Comparison of the Performance of Forward-Looking Imaging Sys...

引用

5th international conference on Information Communication and signal processing, ICICSP 2022

作者： Zhang, Yujie Ma, Hui Xidian University National Lab of Radar Signal Processing Xi'an China

ISBN: (纸本)9781665485890

Forward-looking imaging systems are mainly divided into phased-array (PA) radar and multiple-input-multiple-output (MIMO) radar according to whether the transmitted signals are coherent or not. Since PA radar can improve the signal-to-noise ratio (SNR) through beamforming, while MIMO radar can achieve higher spatial resolution through channel separation at the receiver. In this paper, the noise-robustness and super-resolution performance of the two systems are analyzed. A fair comparison is conducted under the equal conditions, including algorithm, hardware, etc. We use a half-wavelength uniform array to transmit linear frequency modulation (LFM) signals for PA radar and orthogonal signals for MIMO radar. We first establishes signal models of PA system and MIMO system respectively, where the sparse Bayesian learning algorithm is used for the scene imaging. the simulation results show that the imaging quality of phased array radar is better than that of MIMO radar under low SNR, but worse than MIMO radar under high SNR, which shows that the PA radar is more suitable for imaging under low SNR, while MIMO radar is better under high SNR. © 2022 IEEE.

关键词： Radar imaging

来源：评论

学校读者我要写书评

暂无评论

Efficient Implementation to Reduce the Data Size in Big Data Using Classification Algorithm of machine learning 5th

Efficient Implementation to Reduce the Data Size in Big Data...

引用

5th EAI international conference on Big Data Innovation for Sustainable Cognitive Computing, BDCC 2022

作者： RajKumar, V. Priyadharshini, G. Krishnasamy College of Engineering and Technology Cuddalore India

ISBN: (纸本)9783031283239

Big data play an enormous role in the real-world industry, such as financial, banking, government sector, and healthcare, to store the enormous amount of data stored and processed. Here, big data analytics processing develops many applications but also leads to some challenges: data security, data structure, data standardization, and data storage and transfer. Big data are working more number of data to process, and nowadays, the stored data are increased exponentially in terabytes to zeta bytes, so we will not handle those increases by filtering each data to stored classified data value, removing the replicated data and the unnecessary data stored in big data. In this research, we involved big data analytics in machine learning technique (BDML) to reduce the challenges mentioned above using a classification algorithm. they are many types of classification algorithms that are there to predict the outcome of unstructured data. the primary purpose of the research is to reduce the rising size of data stored and sent, improve data security, and create organized data using machine learning techniques. A graphical model shows our aim of research attained with exemplary efficient implementation. In future, we will improve this technique to work with various real-world applications. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data Analytics

来源：评论

学校读者我要写书评

暂无评论

Analysis of Text Classification Using machine learning and Deep learning 5th

Analysis of Text Classification Using Machine Learning and D...

引用

5th international conference on Emerging Technologies in Computer Engineering: Cognitive Computing and Intelligent IoT, ICETCE 2022

作者： Desai, Chitra Department of Computer Science National Defence Academy Pune India

ISBN: (纸本)9783031070112

this paper analyzes the performance of text classification using machine learning and deep learning models. the data is preprocessed, followed by text preprocessing. Natural language processing requires the conversion of text data to numerical vectors before they are passed to machine learning or deep learning models. Bag of words and Term Frequency and Inverse Document Frequency (TFIDF) techniques are used for converting text to a numeric vector. the machine learning models demonstrated are Naïve Bayes Classifier and Logistic Regression. Here, the Bag of words is used with Naïve Bayes Classifier, and TFIDF is used with the logistic regression model. the deep learning models demonstrated here are Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). the data set used consists of 1786 instances. Train test ratio used is 80:20. the performance of text classification models depends upon the dataset and how well its features are preprocessed as well as the selection of train test data. In this paper, four different algorithms are applied to the same dataset to analyze the performance of text classification. © 2022, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Text processing

来源：评论

学校读者我要写书评

暂无评论

machine learning based Radar Heatmap Generation for Advanced Driver Assistance Systems 5

Machine Learning based Radar Heatmap Generation for Advanced...

引用

5th international conference on High Performance Big Data and Intelligent Systems, HDIS 2023

作者： Klassen, Angela Karakuş, Erkan Yang, Qing Dept. of Electrical Computer and Biomedical Engineering University of Rhode Island KingstonRI02881 United States

ISBN: (纸本)9798350394160

Radar sensors are commonly used in Advanced Driver Assistance Systems (ADAS) to detect surrounding objects. Radar signals pass a signal processing chain to compute the range, the velocity and the angular position of potential obstacles and other traffic participants. Major challenges of this procedure are the high complexity and latency of transferring a large amount of raw radar data to subsequent processing units. this paper presents a machine learning model that dramatically reduces the latency of the data transfer by compression of the raw radar data and that generates Range-Angle (RA) Heatmaps directly from the compressed data. RA Heatmaps present the essential visualization technique for the localization of surrounding objects in the radar horizon. In addition, they can be used to detect and identify objects. We use the autoencoder and the U-Net architecture for the compression and the RA Heatmap generation respectively. For the collection of raw radar data, a Texas Instruments (TI) AWR1243 FMCW radar sensor board is utilized. the data to train the U-Net architecture is obtained by applying analytical radar imaging algorithms including a 3-dimensional Fast Fourier Transform (3D FFT) and our proposed framework for Region of Interest (ROI) extraction on the collected data. Experimental results indicate that our final system can achieve a significant reduction of the original raw radar data while still maintaining all relevant features required for object recognition tasks. Excellent accuracy scores exceeding 99 % on input data that has been compressed by a factor of four validate the capabilities of the model and underline its potential for radar data processing in the context of ADAS. ©2023 IEEE.

关键词： Data transfer

来源：评论

学校读者我要写书评

暂无评论

Bacterial Blight and Cotton Leaf Curl Virus Detection Using Inception V4 Based CNN Model for Cotton Crops 5

Bacterial Blight and Cotton Leaf Curl Virus Detection Using ...

引用

5th IEEE international conference on Image processing Applications and Systems (IPAS)

作者： Anwar, Sohail Kolachi, Abdul Rahim Baloch, Shadi Khan Soomro, Shoaib R. Mehran Univ Engn & Technol Dept Elect Engn Jamshoro Pakistan Mehran Univ Engn & Technol Dept Mechatron Engn Jamshoro Pakistan

ISBN: (纸本)9781665462198

Agriculture sector is an important pillar of the global economy. the cotton crop is considered one of the prominent agricultural resources. It is widely cultivated in India, China, Pakistan, USA, Brazil, and other countries of the world. the worldwide cotton crop production is severely affected by numerous diseases such as cotton leaf curl virus (CLCV/CLCuV), bacterial blight, and ball rot. Image processing techniques together with machine learning algorithms are successfully employed in numerous fields and have also used for crop disease detection. In this study, we present a deep learning-based method for classifying diseases of the cotton crop, including bacterial blight and cotton leaf curl virus (CLCV). the dataset of cotton leaves showing disease symptoms is collected from various locations in Sindh, Pakistan. We employ the Inception v4 architecture as a convolutional neural network to identify diseased plant leaves in particular bacterial blight and CLCV. the accuracy of the designed model is 98.26% which shows prominent improvement compared to the existing models and systems.

关键词： cotton crop disease detection CNN CLCV Bacterial Blight detection Image processing

来源：评论

学校读者我要写书评

暂无评论

Defining the Convergence of Artificial Intelligence and Cyber Security with a Case Study of Email Spam Detection 1

引用

5th international conference on Soft Computing and signal processing, ICSCSP 2022

作者： thapliyal, Siddhant Wazid, Mohammad Singh, D.P. Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun248002 India

ISBN: (数字)9789811986697

ISBN: (纸本)9789811986680

In the current era where we deal with a lot of technological advancements, the cyber security frameworks should also be restructured with the help of various artificial intelligence (AI)-based algorithms. As we know currently, there are a number of security threats to the transmitted and stored data. therefore, we cannot secure the data with manual security or loosely coupled algorithms. We need certain automatic and frequent checkups, which can enhance its security. AI is a term which can help us in achieving the same results as we expect. In this paper, we describe certain techniques, which can be used in the field of cyber security. the challenges of implementation of cyber security are highlighted. Further, we discuss the benefits of AI in the field of cyber security. We also provide the AI tools used in cyber security. We have considered the scenario of email spamming and presented a mechanism for the detection of spam emails. the presented scheme achieved better accuracy as compared to the other existing schemes. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： machine learning

来源：评论

学校读者我要写书评

暂无评论

ICECC 2022 - Proceedings of the 5th international conference on Electronics, Communications and Control Engineering

ICECC 2022 - Proceedings of the 5th International Conference...

引用

5th international conference on Electronics, Communications and Control Engineering, ICECC 2022

ISBN: (纸本)9781450395847

the proceedings contain 24 papers. the topics discussed include: AI hardware oriented trojan detection architecture;research on valuation level analysis and prediction method of listed enterprises based on market sales ratio;hand gesture authentication using optimal feature selection and dynamic time warping based K-nearest neighbor;using augmented reality (AR) to educate the student: bridging the communication for Internet addiction;research on the dynamic dispatching algorithm of cloud data center resource;a machine learning based fuel consumption saving method with time and environment dependency aware management;designing secure and scalable end-to-end private network connections between sites via overlay tunnels;design of a hybrid fiber optic coaxial transmission medium;and remote acquisition and processing of cardiac signals using Arduino and MATLAB.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Review on Optimal Deep learning Based Prediction Model for Multi Disease Prediction 1

引用

5th international conference on Smart Technologies in Data Science and Communication, SMART-DSC 2022

作者： Minda, Aneel Kumar Ganesan, Vithya International SOS Dubai United Arab Emirates CSE Koneru Lakshmiah Education Foundation Guntur India

ISBN: (数字)9789811968808

ISBN: (纸本)9789811968792

Healthcare data collecting and processing is one of the most worrisome troublesome to optimize the methodology. With the advent of the digital era and technological advancements, a vast quantity of multidimensional data on patients is created, including clinical factors, hospital resources, illness diagnostic information, patients’ records, and medical equipment. the enormous, dense, and complex data must be processed and evaluated to extract knowledge for effective decision-making. Medical data mining offers a lot of potential for uncovering hidden patterns in medical data sets. By identifying significant patterns and detecting correlations and relationships among many variables in huge databases, the use of various data mining tools and machine learning approaches has changed healthcare organizations. this review paper identifies an importation in the medical data, providing and comparing existing data for the future course of action. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Data science for healthcare Disease predication Health care Health prediction Medical care data analysis

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78页 << < 24 25 26 27 28 29 30 31 32 33 > >>

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：