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

145 篇 会议
1 册 图书
1 篇 期刊文献

馆藏范围

147 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

90 篇 工学
- 72 篇 计算机科学与技术...
- 64 篇 软件工程
- 37 篇 信息与通信工程
- 22 篇 生物工程
- 19 篇 生物医学工程（可授...
- 14 篇 电子科学与技术（可...
- 13 篇 电气工程
- 10 篇 控制科学与工程
- 8 篇 机械工程
- 8 篇 化学工程与技术
- 7 篇 动力工程及工程热...
- 5 篇 仪器科学与技术
- 4 篇 材料科学与工程（可...
- 4 篇 农业工程
- 4 篇 安全科学与工程
56 篇 理学
- 25 篇 数学
- 24 篇 生物学
- 18 篇 物理学
- 8 篇 化学
- 8 篇 系统科学
- 8 篇 统计学（可授理学、...
21 篇 医学
- 20 篇 临床医学
- 19 篇 基础医学(可授医学...
- 14 篇 药学(可授医学、理...
- 4 篇 公共卫生与预防医...
19 篇 管理学
- 11 篇 图书情报与档案管...
- 10 篇 管理科学与工程(可...
- 5 篇 工商管理
4 篇 农学
- 4 篇 作物学
3 篇 经济学
- 3 篇 应用经济学
2 篇 法学
1 篇 教育学
1 篇 军事学

主题

13 篇 machine learning
10 篇 signal processin...
8 篇 deep learning
7 篇 support vector m...
6 篇 electroencephalo...
4 篇 feature extracti...
4 篇 signal processin...
4 篇 machine learning...
4 篇 forecasting
3 篇 object detection
3 篇 websites
3 篇 decision trees
2 篇 covid-19
2 篇 dermatology
2 篇 signal detection
2 篇 task analysis
2 篇 anomaly detectio...
2 篇 neural networks
2 篇 learning algorit...
2 篇 robots

机构

2 篇 school of electr...
2 篇 ugam solutions c...
2 篇 school of comput...
2 篇 guangzhou power ...
2 篇 beijing world yo...
2 篇 tiangong univers...
2 篇 school of electr...
2 篇 school of busine...
2 篇 school of foreig...
2 篇 gitam university...
2 篇 nanjing universi...
2 篇 kiet group of in...
2 篇 department of el...
2 篇 school of econom...
1 篇 school of automa...
1 篇 school of comput...
1 篇 american interna...
1 篇 vit-ap universit...
1 篇 institute of sig...
1 篇 ait-cse chandiga...

作者

2 篇 pandey trilok na...
2 篇 trilok nath pand...
1 篇 tieran zheng
1 篇 zao feifei
1 篇 tyagi tanishqa
1 篇 lei wang
1 篇 aynur nahar urme
1 篇 singh priyank
1 篇 md. ariyan jahan...
1 篇 pangavhane madhu...
1 篇 zhang meifang
1 篇 chen hang
1 篇 junaid abdul man...
1 篇 saqib jahir
1 篇 sletzer concy ma...
1 篇 sathishkumar v.e...
1 篇 al juabir abdull...
1 篇 saroj kumar pani...
1 篇 mishra tasmin
1 篇 lima jose

语言

89 篇 英文
58 篇 其他
3 篇 中文

检索条件"任意字段=3rd International Conference on Signal Processing and Machine Learning, CONF-SPML 2023"

共 147 条记录，以下是121-130 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：

signal processing Grand Challenge 2023 – E-Prevention: Sleep Behavior as an Indicator of Relapses in Psychotic Patients

Signal Processing Grand Challenge 2023 – E-Prevention: Slee...

引用

international conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Kleanthis Avramidis Kranti Adsul Digbalay Bose Shrikanth Narayanan Signal Analysis and Interpretation Lab University of Southern California Los Angeles CA

This paper presents the approach and results of USC SAIL’s submission to the signal processing Grand Challenge 2023 – e-Prevention (Task 2), on detecting relapses in psychotic patients. Relapse prediction has proven to be challenging, primarily due to the heterogeneity of symptoms and responses to treatment between individuals. We address these challenges by investigating the use of sleep behavior features to estimate relapse days as outliers in an unsupervised machine learning setting. We extract informative features from human activity and heart rate data collected in the wild, and evaluate various combinations of feature types and time resolutions. We found that short-time sleep behavior features outperformed their awake counterparts and larger time intervals. Our submission was ranked 3rd in the Task’s official leaderboard, demonstrating the potential of such features as an objective and non-invasive predictor of psychotic relapses.

关键词： Heart rate machine learning Feature extraction Acoustics Behavioral sciences Data mining Task analysis

来源：评论

学校读者我要写书评

暂无评论

An Efficient Face Recognition Method Based on CNN

An Efficient Face Recognition Method Based on CNN

引用

Power Electronics, Computer Applications (ICPECA), IEEE international conference on

作者： Xiu He Feng Ding Guangzhou Xinhua University Guangzhou China

As a prevailing research in artificial intelligence, the application of computer vision is widely used in many fields which are closely related to people's livelihood, such as industrial automation, new retail industry, smart transportation and security monitoring. And the proposed face recognition method is a branch in the field of computer vision, it integrates neural networks, biology, image signal processing, machine learning and other fields, which promote research and cross-development among different disciplines. Hence, this paper focuses on face recognition method by using convolutional neural network(CNN), and CNN has the property of "weight sharing", which has been widely popularized in image recognition, it can greatly simplify the work of large-scale network training. The experiments demonstrate that the proposed face recognition method is successful, and the accuracy of the proposed method can be as high as 98%.

关键词： Training Computer vision Image recognition Image color analysis Face recognition Color signal processing

来源：评论

学校读者我要写书评

暂无评论

A machine learning Model on Healthcare Based Chatbot and Appointment System

A Machine Learning Model on Healthcare Based Chatbot and App...

引用

international Symposium on Artificial Intelligence and signal processing (AISP)

作者： Kushagra Srivastava Trilok Nath Pandey Debaraj Roy Sambit Sahoo School of Computer Science and Engineering Vellore Institute of Technology Chennai India

This paper discusses the clinical chatbot which could examine the contamination and deliver essential insights regarding the contamination previous to counseling a specialist. To lower the healthcare charges and similarly increase openness to clinical facts the clinical chatbot is constructed. Certain chatbots pass approximately as clinical reference books, which facilitates the affected person to discover approximately their contamination and assists with running on their fitness. The person can accomplish the real gain of a chatbot simply while it is able to examine all forms of infections and deliver essential data. In later sections of the paper, a doctor appointment system software is also discussed that is integrated with the chatbot so that the specialist which is recommended by medical chatbot can be easily visited at the mutually agreed time of both specialist and patient. Such an appointment system has its own advantages like it reduces the waiting time of the patient, patients can choose the appointment time in keeping with their desire additionally to be had and booked slots are proven in powerful graphical person interface.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Comprehensive Research on Speaker Recognition and its Challenges

Comprehensive Research on Speaker Recognition and its Challe...

引用

Smart Data Intelligence (ICSMDI), international conference on

作者： Venkata Syama Sowmya Sri Hari Arun Kumar Annavarapu Vamsi Shesamsetti Sathwik Nalla Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Guntur Andhra Pradesh India

The study of speech is a subfield of the measurement of uniquely identifying and measurable patterns in human activity. It communicates details about a person's characteristics. As an illustration, consider gender, age, emotion, and health status. Voice Identification is the process of pointing person purely with the help of vocal pulses. Using voice assistants and smart gadgets as a base, several academics are exploring in this field. This article offers detailed information on speaker recognition. Additionally, a different adversarial technique is described in advance of the well-known machine learning methods. This study provides an overview of the speaker recognition topic by covering its system, modelling approaches, applications, and some underlying theories. The strengths of speaker recognition technologies will be discussed.

关键词： Surveys Deep learning Biometrics (access control) Virtual assistants Biological system modeling Humanoid robots signal processing

来源：评论

学校读者我要写书评

暂无评论

ADBIS: Anomaly Detection to Bolster IoT Security Using machine learning

ADBIS: Anomaly Detection to Bolster IoT Security Using Machi...

引用

international conference on Applied Electromagnetics, signal processing and Communication (AESPC)

作者： Vidhya N P.T.V. Bhuavneswari Department of Electronics Engineering Madras Institute of Technology Anna University Chennai India

The Internet of Things (IoT) represents a transformative technology with profound implications for our daily lives. However, the rapid proliferation of IoT devices has brought about heightened concerns regarding security vulnerabilities. To address these challenges, this research focuses on the application of machine learning (ML) algorithms to detect anomalies in the CTU-IoT dataset, a prominent IoT-based home automation dataset. The methodology entails extracting comma-separated values (.csv) files from packet capture (pcap) data, followed by the removal of outliers using a simple imputer technique. The Isolation Forest algorithm is then utilized to label dataset entries as anomalies or not, with these labels incorporated into the dataset. Given the class imbalance issue that arises, oversampling techniques such as SMOTE (Synthetic Minority Oversampling Technique) and Borderline-SMOTE are employed to balance the dataset. The study encompasses three datasets: the original unbalanced dataset, the SMOTE balanced dataset, and the Borderline-SMOTE dataset. A selection of ML algorithms, including SVM, Naive Bayes, Decision Tree, and Random Forest is applied to these datasets, and their performance is assessed using key metrics like accuracy, precision, recall, F1-score and computation time. The findings reveal that the Decision Tree algorithm outperforms the other three algorithms based on the performance metrics, showcasing its suitability for anomaly detection in the Borderline- SMOTE balanced dataset. This research contributes to strengthening the security and safety of IoT applications.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Information Recommendation of English Oral Teaching Resource Library Based on Collaborative Filtering and Support Vector machine

Information Recommendation of English Oral Teaching Resource...

引用

signal processing, Communications and Engineering Management conference (ISPCEM), international

作者： Hang Chen Meifang Zhang Weiying He School of Information Engineering Guangzhou Vocational College of Technology & Business Guangzhou Guangdong China School of Foreign Languages Guangzhou Institute of Science and Technology Guangzhou Guangdong China School of Computer Science and Engineering Guangzhou Institute of Science and Technology Guangzhou Guangdong China

In order to improve the sharing and real-time access scheduling capabilities of English oral teaching resource library information, a collaborative filtering and support vector machine based English oral teaching resource library information recommendation model is proposed. Using the keyword graph model and text semantic feature detection method to construct an information allocation network structure model for English oral teaching resource library, using collaborative filtering method to achieve keyword feature detection and interference information filtering for English oral teaching resources, and combining support machine classification recognition method to extract semantic keywords from text pairs, Introducing syntax parsing tree and pre trained language model to establish semantic information tree learning in the information recommendation process of English oral teaching resource library, constructing a text graph model based on extracted keywords, fully utilizing the semantic information tree of the text to pair the recommendation information between learning nodes and neighboring nodes, and inputting the generated text sequence into the recommendation sequence vector table, Combining collaborative filtering method and support vector machine algorithm to achieve information recommendation for English oral teaching resource library. The simulation results show that this method has good feature matching ability for recommending information in the English oral teaching resource library, with an Fl of 87.3 % on datasets such as CNSE. It has strong filtering ability for mixed information in the context of English oral resources, and improves the ability to accurately recommend information.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Pre Cardiac Failure Detection using different supervised machine learning Methods with CNN

Pre Cardiac Failure Detection using different supervised Mac...

引用

international Symposium on Artificial Intelligence and signal processing (AISP)

作者： Amit Gupta Meeravali Shaikh G. Jithender Reddy Arun Singh Chouhan Department of Cyber Security School of Engineering Malla Reddy University Telangana Department of CSE School of Engineering Malla Reddy University Telangana GITAM University Visakhapatnam

For aspect, a convolution Neural Network (CNN) for cardiac arrest would help establish a better output. Whilst a cardiac arrest occurs, the limited interventions available to shop-affected person’s lives are related to badly affected outcomes. Therefore, the best way to enhance affected person results and lower related healthcare prices might be to prevent cardiac arrest. This remark highlights the significance of prediction models that continuously perceive excessive-risk individuals and assist healthcare providers in providing centered care to the appropriate patient at the appropriate time for the early identification of cardiac arrest patients who may need immediate medical attention. Moreover, the significant aspect lies in the proper symmetry formation or can, say, the better scenario to compute or make a clear recognition of the image having a clear resolution of the image. Starting with a small model to determine things as simple as CNN (Convolution Neural Network). In this proposed paper, we are used in seven different supervised machine learning method for simulation of ECG data set results in different time interval with different duration and amplitude. In the CNN with a partially connected convolution layer, the image has a single neuron connected to a small layer region. The CNN (convolution Neural Network) image classification takes the input, processes it and classification is done on the dimensions organized in three dimensions width, height, and depth.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Screening of Citrus Diseases Using Deep learning Embedders and machine learning Techniques

Screening of Citrus Diseases Using Deep Learning Embedders a...

引用

international Symposium on Artificial Intelligence and signal processing (AISP)

作者： Yagnesh Challagundla Lohitha Rani Chintalapati Trilok Sai Charan Tunuguntla Amit Sur Bappadittya Roy Eugenia R. Zhuo School of Computer Science & Engineering VIT-AP University Amaravati Andhra Pradesh India Department of IT HIT West Bengal India VIT-AP University School of Electronics Amaravati Andhra Pradesh India College of Information and Computing Sciences University of Santo Tomas Manila Philippines

A tropical fruit with great economic significance, citrus is cultivated and farmed in almost 150 different nations. A total of about 157.98 million tons of citrus fruit are produced worldwide. Citrus plant diseases have a major negative impact on the citrus fruit market as well as production in terms of quantity as well as quality. Attention must be paid to citrus fruits and leaves in order to promptly diagnose and treat problems; failing to do so results in severe financial loss. Citrus plant diseases cause a yearly loss of about 50% of citrus fruits at citrus farming operations. In this study, to produce the vector representation of the images, we used three deep learning image embedders namely Inception V3, VGG16, and Squeeze net. We used five machine learning models, including Random Forest, KNN, Gradient Boosting, SGD, and Neural Network with 5-fold Cross Validation, to predict citrus diseases. Using the considered dataset, the classification performance of each independently tuned ML model across all of its ensembles has been obtained. The neural network with Inception V3 as image embedder has obtained maximum average accuracy of 96.6%, 96.6% recall, 96.5% precision, and 96.5% F1 Score. Finally, our prediction model offers a reliable technique for accurate detection of citrus diseases to assist farmers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

machine learning based human recognition via robust Features from audio signals

Machine Learning based human recognition via robust Features...

引用

Artificial Intelligence (ICAI), international conference on

作者： Umar Sadique Muhammad Suleman Khan Shahzad Anwar Mehran Ahmad AI in Healthcare Lab National Centre of AI University of Engineering and Technology Peshawar Pakistan Department of Electrical Engineering University of Engineering and Technology Peshawar Pakistan Department of Mechatronics Engineering University of Engineering and Technology Peshawar Pakistan

Biometric verification techniques are commissioned throughout the world in different applications. Human voice recognition is one of the biometric techniques. This technique consists of identifying a human from their voice characteristic. This popular and beneficial biometric technique could be employed for identity human, security purposes, and many different applications. Human audio signal recognition consists of two phases i.e., Features Extraction and Classification. The proposed work consists of extracting features through the Mel Frequency Cepstral-Coefficient (MFCC) from the human audio signal, selecting robust features through Principal Component Analysis PCA, and classifying the selected features by comparing seven machine learning and proposed deep learning algorithms. Finally, compare the performance of different algorithms with different percentages of selected features to evaluate the acceptance rate of the correlated features. Support Vector machine SVM shows the best performance with an Accuracy of 99.27% with F1-score and ROC values of 1.00. In the comparison with other methods, the Random Forest and CNN-ANN are 2 nd top robust models with an accuracy of 98.7%. Some of the algorithm's accuracy decreased with fewer features, including Naïve Bayes accuracy suddenly decreases to 60% on 20% of total features. The experiment concludes the acceptance rate of correlated features in different ML and DL algorithms are different in speech processing data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Diabetes Prediction Using Nature-Inspired Optimization Algorithms

Diabetes Prediction Using Nature-Inspired Optimization Algor...

引用

international Symposium on Artificial Intelligence and signal processing (AISP)

作者： J. Vijaya Divyanshu Tirkey Priyank Singh Aditya Goel Department of DSAI International Institute of Information Technology Naya Raipur chhattisgarh

Diabetes is a common genetic disease across the world. It is a chronic disease spurred by either production of insufficient production of insulin by the pancreas or less insulin use by the body. Insulin maintains the blood sugar level of the body. Uncontrolled diabetes can cause hypertension, also known as high blood glucose. Hypertension in the long run can be a cause of heart disease. Therefore, the prediction of diabetes is a major problem in the health sector. Various machine learning methods are already in use for the prediction of diabetes. Traditional methods were first used to address diabetes forecasting, but they take a while to deploy. Therefore, future research has adopted the use of various optimization strategies to solve the issue of diabetes forecasting as well as to boost system selectivity and operating speed. These methods have all proven to be successful in solving different optimization issues and also improve the model significantly. This work proposes a Logistic Regression model by the use of nature-inspired algorithms. We proposed a methodology which uses seven different optimization algorithms instead of gradient descent for linear regression. We implemented a linear regression algorithm from scratch and then used it with different optimization algorithms which improve the overall performance.

关键词：

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15页 << < 6 7 8 9 10 11 12 13 14 15 > >>

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：