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

1,327 篇 会议
11 篇 期刊文献
9 册 图书

馆藏范围

1,347 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

915 篇 工学
- 757 篇 计算机科学与技术...
- 498 篇 软件工程
- 303 篇 信息与通信工程
- 204 篇 电气工程
- 175 篇 生物工程
- 127 篇 生物医学工程（可授...
- 107 篇 光学工程
- 90 篇 控制科学与工程
- 80 篇 电子科学与技术（可...
- 58 篇 仪器科学与技术
- 48 篇 机械工程
- 35 篇 化学工程与技术
- 28 篇 安全科学与工程
- 26 篇 交通运输工程
425 篇 理学
- 189 篇 生物学
- 187 篇 数学
- 151 篇 物理学
- 76 篇 统计学（可授理学、...
- 54 篇 系统科学
- 40 篇 化学
169 篇 管理学
- 106 篇 图书情报与档案管...
- 72 篇 管理科学与工程(可...
- 40 篇 工商管理
146 篇 医学
- 130 篇 临床医学
- 88 篇 基础医学(可授医学...
- 65 篇 药学(可授医学、理...
- 24 篇 公共卫生与预防医...
28 篇 教育学
- 28 篇 教育学
27 篇 法学
- 21 篇 社会学
18 篇 经济学
- 17 篇 应用经济学
16 篇 农学
5 篇 军事学
1 篇 文学
1 篇 历史学

主题

210 篇 machine learning
134 篇 deep learning
78 篇 signal processin...
71 篇 accuracy
70 篇 feature extracti...
68 篇 signal processin...
61 篇 support vector m...
56 篇 machine learning...
45 篇 predictive model...
33 篇 neural networks
32 篇 convolutional ne...
31 篇 random forests
29 篇 computational mo...
29 篇 training
26 篇 natural language...
25 篇 prediction algor...
21 篇 technological in...
20 篇 real-time system...
19 篇 adversarial mach...
18 篇 image processing

机构

16 篇 chitkara centre ...
14 篇 centre of resear...
12 篇 shenyang ligong ...
6 篇 chitkara univers...
6 篇 ai & ds vishwaka...
6 篇 school of inform...
5 篇 department of me...
5 篇 khulna universit...
5 篇 department of co...
4 篇 delhi technologi...
4 篇 heilongjiang uni...
4 篇 department of s&...
4 篇 beijing univ pos...
4 篇 it vishwakarma i...
4 篇 chitkara univers...
4 篇 sri lanka instit...
4 篇 advanced telecom...
4 篇 shenyang ligong ...
4 篇 graduate school ...
3 篇 karunya institut...

作者

6 篇 mehta shiva
5 篇 rasmita panigrah...
4 篇 neelamadhab padh...
4 篇 wang xin
3 篇 m. vigenesh
3 篇 baydeti nagaraju
3 篇 sinambela marzuk...
3 篇 santosh kumar sh...
3 篇 ganapati panda
3 篇 debendra muduli
3 篇 abujar sheikh
3 篇 a. sivanantham
3 篇 li yajie
3 篇 li aihua
3 篇 zhou feng
3 篇 islam md. sanzid...
2 篇 aira kharvel par...
2 篇 nokshangthemba
2 篇 maheswara rao v ...
2 篇 lee tzong-ru

语言

1,187 篇 英文
151 篇 其他
11 篇 中文

检索条件"任意字段=Proceedings of the 2019 2nd International Conference on Signal Processing and Machine Learning"

共 1347 条记录，以下是541-550 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：

HYBRID MODEL FOR NETWORK ANOMALY DETECTION WITH GRADIENT BOOSTING DECISION TREES And TABTRANSFORMER

HYBRID MODEL FOR NETWORK ANOMALY DETECTION WITH GRADIENT BOO...

引用

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

作者： Xu, Xinyue Zheng, Xiaolu Australian Natl Univ Canberra ACT Australia Beihang Univ Beijing Peoples R China

ISBN: (纸本)9781728176055

Last decades have witnessed the monumental growth of Internet applications, and the network security fields have attracted increasing interests as it has become a necessity due to proliferation of information technologies in everyday life. Network anomaly detection aims to detect the potential anomalous behavior in traffic data, which is critical for detecting and reacting to the presence of attacks in the network. In this paper, we present our solution for the ICASSP 2021 Network Anomaly Detection Challenge (NAD) challenge. Firstly, we present our feature extraction method in detecting network anomalies, as efficiently extracting the discriminate features from the traffic data over time can be greatly helpful to improve the anomaly detection performance. Secondly, both gradient boosting decision trees and TabTransformer-Based classification model are trained for the multi-class classification task. The TabTransformer is based on self-attention and can transform the categorical feature' embeddings into robust contextual embeddings, thus, can achieve higher prediction accuracy. Finally, we ensemble the results to improve the performance further. To demonstrate the effectiveness of our approach, extensive experiments have been conducted on the NAD datasets. Our approach achieves the score of 0.625 and ranked as 2nd place in the final leaderboard.

关键词： Network anomaly detection Gradient Boosting Decision Trees TabTransformer Self-attention Ensemble learning

来源：评论

学校读者我要写书评

暂无评论

A Web Based Four-Tier Architecture using Reduced Feature Based Neural Network Approach for Prediction of Student Performance 2

A Web Based Four-Tier Architecture using Reduced Feature Bas...

引用

2nd international conference on Robotics, Electrical and signal processing Techniques, ICREST 2021

作者： Hossen, Anwar Alamgir, Rakib Bin Alam, Arman Ul Siddika, Fatema Hossain, Shah Fahad Arman, Md. Shohel Daffodil International University Dept. of Software Engineering Dhaka Bangladesh Jagannath University Dept. of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665415767

Enhancing student's performance is a significant part of developing quality education in any educational institute. It is very difficult to get promising student performance without student categorization according to their academic performance as there are different standardized students. In this paper, our aim is to determine the performance of the students. For this purpose, a survey has been conducted on students in our university in order to collect data and to analyze and predict the student category based on their performance. Apart from this, another purpose of this study is to examine the effect of the reduced features on the classification model using state-of-art machine learning algorithms. Here, we propose a workflow of web-based four-tier architecture for the student performance prediction that will define the student's category in order to help them exactly pinpoint their learning capabilities. Hence, we used multiple supervised learning-based machine learning techniques for the prediction of student performance. Each of the student category categorized by considering on the top features. The analysis results indicate that we got the highest performance that is 88.00% by using the Artificial Neural Network (ANN) among the classifiers by showing its superiority to the existing model. © 2021 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Cyber Attack Detection Model (CADM) Based on machine learning Approach 2

Cyber Attack Detection Model (CADM) Based on Machine Learnin...

引用

2nd international conference on Robotics, Electrical and signal processing Techniques, ICREST 2021

作者： Hossain, Fahima Akter, Marzana Uddin, Mohammed Nasir Jagannath University Department of Computer Science and Engineering Dhaka1100 Bangladesh

ISBN: (纸本)9781665415767

A reliable Cyber Attack Detection Model (CADM) is a system that works as safeguard for the users of modern technological devices and assistant for the operators of networks. The research paper aims to develop a CADM for analyzing the network data patterns to classify cyber-attacks. CADM finds out attack wise detection accuracy using ensemble classification method. LASSO has been used to extract important features. It can work with large datasets and it has more visualization capability. Gradient Boosting and Random Forest algorithms have been used for classification of network traffic data to build an ensemble method. Gradient Boosting algorithm trains weak learning models and select the best decision trees to deliver more improved prediction accuracy and Random Forest algorithm trains each tree in parallel manner. In this research work, five datasets such as NSL-KDD, KDD Cup 99, UNSWNB15, URL 2016 and CICIDS 2017 are also applied to check the efficiency of the proposed model. © 2021 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

A Study on Banana Leaf Disease Detection Based on Grabcut Algorithm Using Multispectral Camera

A Study on Banana Leaf Disease Detection Based on Grabcut Al...

引用

international conference on signal processing, Communication, Power and Embedded System (SCOPES)

作者： N. Jeebaratnam Chinmayee Dora Dhawaleswar Rao CH Electronics and Communication Engineering Centurion University of Technology and Management Paralakhemundi India Computer Science Engineering Centurion University of Technology and Management Paralakhemundi India

ISBN: (数字)9798331506452

ISBN: (纸本)9798331506469

The majority of people in India rely on farming as their primary source of income. Farmers encounter a variety of difficulties as a result of climate change. Decrease in yield is due to diseases on the plant. The quickest and easiest way must be used to identify the illness. machine learning and image processing techniques are mostly used to automatically identify the diseases. In this article examined a method for diagnosing diseases in banana plants, structure, Pigment and surface. In this paper, a novel Henry Gas based Grab Cut (HGGC) algorithm by the integration of the Henry Gas Solubility Optimization algorithm (HGSO) and Grab Cut (GC) algorithm to detect the disease in the banana plant using multi spectral camera. Initially, the pre-processing is done by using a median filter for the removal of noises in the image. The segmentation is carried out using a region-based edge normalization after the images have been pre-processed using a median filter. Here, a new integrated system is developed for feature extraction combining Convolutional Neural Networks (CNN). In order to improve disease diagnostic accuracy, a region-based convolution neural network is utilized to detect the disease area by extracting and classifying information. Additionally, CNN is used to retrieve relevant attributes from the raw intake photographs so that the DL models can be trained. Consequently, the proposed approach is implemented in the PHYTHON framework. The efficiency of the developed HGGC is then demonstrated using tables and graphs by comparing the performance measures with existing methods. Accordingly, the proposed model achieved a better result by utilizing accuracy, sensitivity, specificity and false detection rate when compared to the existing methods.

关键词： Plant diseases Accuracy signal processing algorithms Filtering algorithms Feature extraction Cameras Convolutional neural networks Data mining Optimization Surface treatment

来源：评论

学校读者我要写书评

暂无评论

COVID-19 Detection from Chest X-ray Images Using 2D-LWP-EWT and SVM

COVID-19 Detection from Chest X-ray Images Using 2D-LWP-EWT ...

引用

Innovations in High Speed Communication and signal processing (IHCSP), international conference on

作者： Ranveer Pratap Lal Bhupendra Singh Kirar Dheeraj Kumar Agrawal Vivek Patel Mamta Patankar Raghvendra Singh Thakur Advanced Micro Devices (AMD) USA ECE Department Indian Institute of Information Technology Bhopal India ECE Department Maulana Azad National Institute of Technology Bhopal India Department of CSE IES Institute of Technology and Management Bhopal India

ISBN: (数字)9798350368949

ISBN: (纸本)9798350368956

The global surge of COVID-19, an unprecedented viral outbreak originating in China in 2019, method, real-time reverse transcriptase-polymerase chain reaction (RT-PCR), though widely used, is critiqued for its lower sensitivity and prolonged detection time. This necessitates the development of more sensitive, accurate, and rapid screening techniques for mass application. Recent research suggests that chest X-ray images (CXRIs) can offer heightened sensitivity in COVID-19 detection. This paper proposes an image processing and decomposition-based approach to enhance the performance of COVID-19 detection from CXRIs. Leveraging the Two-dimensional Littlewood Paley Empirical Wavelet Transform (2D-LWP-EWT), the pre-processed image is decomposed into sub-band images (SBIs). Features extracted from these SBIs undergo post-processing (concatenation, normalization, selection, and singular value decomposition) before classification by a support vector machine (SVM). With impressive parameters 98.34% accuracy, 100% sensitivity, 96.67% specificity, 97.50% precision, and 98.57 F-Score obtained through 10-fold cross-validation (FCV), this method outperforms existing COVID-19 detection techniques.

关键词： COVID-19 Support vector machines Wavelet transforms Technological innovation Sensitivity Accuracy Feature extraction Surges X-ray imaging Biomedical imaging

来源：评论

学校读者我要写书评

暂无评论

Detecting Malicious Insiders In Social Networks And Mitigating Cyber Threats With Advanced Security Approaches

Detecting Malicious Insiders In Social Networks And Mitigati...

引用

Innovations in High Speed Communication and signal processing (IHCSP), international conference on

作者： V. Mahalakshmi Avni Garg Rekha M M Mandar Diwakar M. Vigenesh Raman Verma Department of EEE Prince Shri Venkateshwara Padmavathy Engineering College Chennai Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India School of Sciences Chemistry and Biochemistry JAIN (Deemed to be University) Bangalore Karnataka India AI & Ds Vishwakarma Institute of Technology Pune India Department of Computer Science Engineering Karpagam Academy of Higher Education Coimbatore Centre of Research Impact and Outcome Chitkara University Rajpura Punjab India

ISBN: (数字)9798350368949

ISBN: (纸本)9798350368956

When a fraudster uses a false identity to appear as a reliable source in an OSN, this kind of assault is known as an insider attack. The identification of users' actions inside the network is now a popular use of machine learning (ML) techniques. This study introduces Social Network Malicious Insider Detection (SID), a hybrid method that combines LSTM and TBTE. By keeping tabs on user data, the proposed SID hopes to spot data anomalies in OSN interactions. To accurately forecast user behaviour and detect the abnormality pattern in OSN, the suggested SID use LSTM, a more sophisticated kind of Recurrent Neural Network (RNN). A time-based trust assessment approach is used with the LSTM to distinguish between new users, broken nodes, and malicious nodes in OSNs, as well as to accurately classify anomalous nodes. In addition to effectively detecting insider assaults, the proposed SID also decreases wrong apprehensions by offering a new measurable investigation for calculating the corresponding factor over time. This analysis prevents the mistaken characterization of legitimate user behaviours as abnormalities. In comparison to the preexisting RNN, LSTM, and Bilateral LSTM, the suggested SID achieves a greater detection accuracy, according to the evaluation results.

关键词： Training Technological innovation Accuracy Recurrent neural networks Social networking (online) Statistical analysis signal processing Time measurement Long short term memory Testing

来源：评论

学校读者我要写书评

暂无评论

The Influence and Reconstruction of international MOOCS on Chinese College English Curriculum 2

The Influence and Reconstruction of International MOOCS on C...

引用

2nd international conference on Computers, Information processing and Advanced Education, CIPAE 2021

作者： Kang, Weijie Heilongjiang University of Technology Heilongjiang Jixi China

ISBN: (纸本)9781665426657

This paper firstly introduces MOOCS (Massive Open Online Courses) and its main characteristics, then it analyzes the challenges of MOOCS to college English Curriculum in China. This paper discusses the reconstruction of College English Curriculum in China: open classroom, elective College English curriculum;flipped classroom, new-style college English teaching method;renewing concept, professionalization of College English teachers. © 2021 IEEE.

关键词： Computers Computer aided instruction Electronic learning Education Buildings Curriculum development Information processing

来源：评论

学校读者我要写书评

暂无评论

Application of learning Behavior Analysis Algorithm Based on Data Mining in the Cultivation of international Talents 2

Application of Learning Behavior Analysis Algorithm Based on...

引用

2nd international conference on Computers, Information processing and Advanced Education, CIPAE 2021

作者： Wu, Zhong Zhou, Chuan Physical Education School Wuhan Business University Wuhan China Institute of Machanical Engineering Wuhan Institute of Shipbuilding Technology Wuhan China

ISBN: (纸本)9781665426657

In recent years, data mining, as a wide range of applications, has emerged and been widely used in various fields. At present, the role of data mining in the field of learning is on the rise. The main problem of analyzing learning management is that different learners have different styles and behaviors. We need to evaluate the system from all aspects. In the existing teaching methods, more attention is paid to the evaluation of learners. This paper discusses the evaluation of learning management system, and puts forward a new evaluation method of learning management system. The results show that there are 72 active learners and 31 intuitive learners. © 2021 IEEE.

关键词： Training Computers learning management systems Electronic learning Data analysis Education Information processing

来源：评论

学校读者我要写书评

暂无评论

COVID-19 Detection using Transfer learning with Convolutional Neural Network 2

COVID-19 Detection using Transfer Learning with Convolutiona...

引用

2nd international conference on Robotics, Electrical and signal processing Techniques, ICREST 2021

作者： Dutta, Pramit Roy, Tanny Anjum, Nafisa Chittagong University of Engineering and Technology Department of Electronics and Telecommunication Engineering Chittagong Bangladesh

ISBN: (纸本)9781665415767

The Novel Coronavirus disease 2019 (COVID-19) is a fatal infectious disease, first recognized in December 2019 in Wuhan, Hubei, China, and has gone on an epidemic situation. Under these circumstances, it became more important to detect COVID-19 in infected people. Nowadays, the testing kits are gradually lessening in number compared to the number of infected population. Under recent prevailing conditions, the diagnosis of lung disease by analyzing chest CT (Computed Tomography) images has become an important tool for both diagnosis and prophecy of COVID-19 patients. In this study, a Transfer learning strategy (CNN) for detecting COVID-19 infection from CT images has been proposed. In the proposed model, a multilayer Convolutional neural network (CNN) with Transfer learning model Inception V3 has been designed. Similar to CNN, it uses convolution and pooling to extract features, but this transfer learning model contains weights of dataset Imagenet. Thus it can detect features very effectively which gives it an upper hand for achieving better accuracy. © 2021 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Training Optimization for a Hardware-Aware Approach to Deep learning 2nd

Training Optimization for a Hardware-Aware Approach to De...

引用

2nd international conference on Data Science, machine learning and Applications, ICDSMLA 2020

作者： Asok, Anjana Birla Institute of Technology and Science Pilani Rajasthan333031 India

ISBN: (纸本)9789811636899

Deep Convolutional Neural Networks (DCNNs) have been proven to be effective for various problems involving image, video and signal processing and classification. The size and complexity of the network are major concerns when it comes to real-life implementations of DCNNs. The increase in the number of parameters and a consequent increase in power and memory requirement have to be dealt with, for the hardware implementation of these networks. The quantization of parameters conceived as a method to reduce memory requirement has a trade-off on accuracy, and therefore various parameters have to be explored to get to a middle ground. The paper is divided in two parts - The first part explores the techniques to improve upon accuracy and to result in better generalization, for a deep convolutional neural network developed in MATLAB and the second section of the paper presents a comparison and usage of a scalable, efficient algorithm based on the Tensorflow library that does the feature extraction of the MNIST dataset as compared to the algorithm in MATLAB that performs the classification. The performance improvement is in terms of time-efficiency in training, an improved accuracy rate and a highly parallel algorithm that does effective classification. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feature extraction

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135页 << < 51 52 53 54 55 56 57 58 59 60 > >>

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：