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

104 篇 学位论文
7 篇 期刊文献
1 篇 会议

馆藏范围

112 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

5 篇 工学
- 3 篇 计算机科学与技术...
- 1 篇 仪器科学与技术
- 1 篇 电气工程
- 1 篇 控制科学与工程
- 1 篇 环境科学与工程（可...
3 篇 管理学
- 3 篇 工商管理
- 2 篇 管理科学与工程(可...
2 篇 理学
- 1 篇 化学
- 1 篇 天文学
- 1 篇 大气科学
- 1 篇 地球物理学
- 1 篇 地质学
- 1 篇 生物学
1 篇 教育学
- 1 篇 心理学(可授教育学...

主题

112 篇 artificial intel...
25 篇 other computer s...
17 篇 deep learning
17 篇 computer science...
16 篇 machine learning
14 篇 information secu...
12 篇 databases and in...
6 篇 graphics and hum...
5 篇 theory and algor...
5 篇 computer vision
4 篇 svm
4 篇 neural networks
4 篇 yolo
3 篇 reinforcement le...
3 篇 robotic competit...
3 篇 software enginee...
3 篇 natural language...
3 篇 cnn
3 篇 os and networks
3 篇 bioinformatics

机构

59 篇 san jose state u...
24 篇 university of ma...
2 篇 california polyt...
2 篇 georgia southern...
2 篇 new jersey insti...
2 篇 university of co...
1 篇 amity univ amity...
1 篇 univ nottingham ...
1 篇 western michigan...
1 篇 department of co...
1 篇 wayne state univ...
1 篇 edith cowan univ...
1 篇 univ groningen c...
1 篇 autonomous intel...
1 篇 department of re...
1 篇 univ south pacif...
1 篇 univ chile dept ...
1 篇 university of ne...
1 篇 natl univ sci & ...
1 篇 faculty of envir...

作者

1 篇 ha le thanh
1 篇 ashraf saber
1 篇 komei sugiura
1 篇 niket bhodia
1 篇 anish hemant nar...
1 篇 samanvitha basol...
1 篇 neha atul bhagwa...
1 篇 jr anthony s bus...
1 篇 nicholas a russo
1 篇 preethi sundarav...
1 篇 michael j. brice
1 篇 takeshi takahash...
1 篇 iocchi luca
1 篇 siddharth kumar
1 篇 afaq anam
1 篇 liu yang
1 篇 hurt jason lee
1 篇 muthaiah ramanat...
1 篇 natesh ganesh
1 篇 mehtab iqbal

语言

112 篇 英文

检索条件"主题词=artificial intelligence and robotics"

共 112 条记录，以下是81-90 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：

A Study of Face Embedding in Face Recognition

A Study of Face Embedding in Face Recognition

引用

作者： Le, Khanh Duc California Polytechnic State University

学位级别：M.Sc., Master of Science

Face Recognition has been a long-standing topic in computer vision and pattern recognition field because of its wide and important applications in our daily lives such as surveillance system, access control, and so on. The current modern face recognition model, which keeps only a couple of images per person in the database, can now recognize a face with high accuracy. Moreover, the model does not need to be retrained every time a new person is added to the database. By using the face dataset from Digital Democracy, the thesis will explore the capability of this model by comparing it with the standard convolutional neural network based on pose variations and training set sizes. First, we compare different types of pose to see their effect on the accuracy of the algorithm. Second, we train the system using different number of training images per person to see how many training samples are actually needed to maintain a reasonable accuracy. Finally, to push the limit, we decide to train the model using only a single image per person with the help of a face generation technique to synthesize more faces. The performance obtained by this integration is found to be competitive with the previous results, which are trained on multiple images.

关键词： Neural Network Computer Vision Machine Learning artificial intelligence and robotics Software Engineering

来源：评论

学校读者我要写书评

暂无评论

Measuring Malware Evolution Using Support Vector Machines

Measuring Malware Evolution Using Support Vector Machines

引用

作者： Mayuri Wadkar San Jose State University

学位级别：硕士

Malware is software that is designed to do harm to computer systems. Malware often evolves over a period of time as malware developers add new features and fix bugs. Thus, malware samples from the same family from different time periods can exhibit significantly different behavior. Differences between malware samples within a single family can originate from various code modifications designed to evade signature-based detection or changes that are made to alter the functionality of the malware itself. In this research, we apply feature ranking based on linear support vector machine (SVM) weights to identify, quantify, and track changes within malware families over time. We analyze numerous malware families over an extended period of time. Our goal is to detect and analyze evolutionary changes over a wide variety of malware families using quantifiable and automated machine learning techniques.

关键词： malware evolution svm artificial intelligence and robotics Information Security

来源：评论

学校读者我要写书评

暂无评论

Influence Analysis Based On Political Twitter Data

Influence Analysis Based On Political Twitter Data

引用

作者： Jace Rose San Jose State University

学位级别：硕士

Studies of online behavior often consider how users interact online, their posting behaviors, what they are tweeting about, and how likely they are to follow other people. The problem is there is that no deeper study on the people that a user has interacted with and how these other users affect them. This study examines if it is possible to draw similar sentiment from users with whom the target user has interacted with. The data collection process gathers data from Twitter users posting to popular political hashtags, which the highest at the time published wereMAGA and #TRUMP, as well as the tweets of people to whom they have tweeted. By applying weights based on the type of interactions as well as the amount, study how close the sentiments that the original user expressed are compared to the users they tweeted to. The weighting formula described above will be known as the Inferred Sentiment Score, or ISS for short. This study presents this scheme of gathering data to build user profiles and ISS to determine how similar a userâs sentimental expression is to the people they communicate with on Twitter. The main results of this study show that by using the ISS formula that there is a strong correlation of the sentiments expressed on Twitter by a user and the users that they communicate with.

关键词： Twitter Sentiment User relationship Stanford NLP artificial intelligence and robotics Databases and Information Systems

来源：评论

学校读者我要写书评

暂无评论

Regression Tree Construction For Reinforcement Learning Problems With A General Action Space

Regression Tree Construction For Reinforcement Learning Prob...

引用

作者： Jr Anthony S Bush Georgia Southern University

学位级别：硕士

Part of the implementation of Reinforcement Learning is constructing a regression of values against states and actions and using that regression model to optimize over actions for a given state. One such common regression technique is that of a decision tree; or in the case of continuous input, a regression tree. In such a case, we fix the states and optimize over actions; however, standard regression trees do not easily optimize over a subset of the input variables\cite{Card1993}. The technique we propose in this thesis is a hybrid of regression trees and kernel regression. First, a regression tree splits over state variables at a macro level, then kernel regression models the effects of actions with a smooth function at a micro level. Then non-linear optimization is used to optimize the kernel regressed function to find the best action and get a precise prediction of its value for any given state. This ``best action" is then stored in the tree and is instantly retrieved upon making decisions. This is not only more appropriate for problems with continuous output, but also for problems with a discrete output since it also generalizes the knowledge over actions as well as states, providing for smarter decision-making. The capabilities of this technique are observed for a time series constructed to realistically model a stock problem.

关键词： Time series analysis Reinforcement learning Machine learning Q-learning Regression trees Kernel regression artificial intelligence and robotics Finance and Financial Management Other Statistics and Probability

来源：评论

学校读者我要写书评

暂无评论

Javascript Metamorphic Malware Detection Using Machine Learning Techniques

Javascript Metamorphic Malware Detection Using Machine Learn...

引用

作者： Aakash Wadhwani San Jose State University

学位级别：硕士

Various factors like defects in the operating system, email attachments from unknown sources, downloading and installing a software from non-trusted sites make computers vulnerable to malware attacks. Current antivirus techniques lack the ability to detect metamorphic viruses, which vary the internal structure of the original malware code across various versions, but still have the exact same behavior throughout. Antivirus software typically relies on signature detection for identifying a virus, but code morphing evades signature detection quite effectively. JavaScript is used to generate metamorphic malware by changing the codeâs Abstract Syntax Tree without changing the actual functionality, making it very difficult to detect by antivirus software. As JavaScript is prevalent almost everywhere, it becomes an ideal candidate language for spreading malware. This research aims to detect metamorphic malware using various machine learning models like K Nearest Neighbors, Random Forest, Support Vector Machine, and NaiÌve Bayes. It also aims to test the effectiveness of various morphing techniques that can be used to reduce the accuracy of the classification model. Thus, this involves improvement on both fronts of generation and detection of the malware helping antivirus software detect morphed codes with better accuracy. In this research, JavaScript based metamorphic engine reduces the accuracy of a trained malware detector. While N-gram frequency based feature vectors give good accuracy results for classifying metamorphic malware, HMM feature vectors provide the best results.

关键词： Javascript malware detection HMM knn random forest SVM naive bayes artificial intelligence and robotics Information Security

来源：评论

学校读者我要写书评

暂无评论

Topic Classification Using Hybrid Of Unsupervised And Supervised Learning

Topic Classification Using Hybrid Of Unsupervised And Superv...

引用

作者： Jayant Shelke San Jose State University

学位级别：硕士

There has been research around the idea of representing words in text as vectors and many models proposed that vary in performance as well as applications. Text processing is used for content recommendation, sentiment analysis, plagiarism detection, content creation, language translation, etc. to name a few. Specifically, we want to look at the problem of topic detection in text content of articles/blogs/summaries. With the humungous amount of text content published each and every minute on the internet, it is imperative that we have very good algorithms and approaches to analyze all the content and be able to classify most of it with high confidence for further use. The project aims to work with unsupervised and supervised machine learning algorithms in an effort to tackle the topic detection problem. The project will target various unsupervised learning algorithms like Word2vec, doc2vec and LDA for corpus and language dictionary learning to have a trained model which understand the semantic of texts. The objective of the project is to combine this unsupervised learning with supervised learning algorithms like Support Vector Machine and deep learning methods to analyze and hopefully better the performance in terms of accuracy of topic detection. The project also aims at performing user interest-based modelling, which is orthogonal to topics modeling. The idea is to make sure the model is free of predefined categories. The project results show that hybrid models are comfortably accurate when classifying text in a particular topic category. The project also concludes that user interest modelling can also be accurately achieved along with topic detection. The project successfully determines these results without any meta information about the input text and purely based on the corpus of the input text. This makes the project framework really robust as it has no dependency on source of text, length of text or any other meta information about the text content.

关键词： opic detection topic modeling hybrid topic mixtures SVM neural network doc2vec LDA. artificial intelligence and robotics Databases and Information Systems

来源：评论

学校读者我要写书评

暂无评论

Differential Estimation Of Audiograms Using Gaussian Process Active Model Selection

Differential Estimation Of Audiograms Using Gaussian Process...

引用

作者： Trevor Larsen Washington University in St. Louis

学位级别：硕士

Classical methods for psychometric function estimation either require excessive resources to perform, as in the method of constants, or produce only a low resolution approximation of the target psychometric function, as in adaptive staircase or up-down procedures. This thesis makes two primary contributions to the estimation of the audiogram, a clinically relevant psychometric function estimated by querying a patientâs for audibility of a collection of tones. First, it covers the implementation of a Gaussian process model for learning an audiogram using another audiogram as a prior belief to speed up the learning procedure. Second, it implements a use case of Bayesian active model selection to determine whether two audiograms differ. Both algorithms were tested using audiometric data from the National Institute for Occupational Safety and Health (NIOSH).

关键词： Audiogram Machine Learning Gaussian Process Model Selection Bayesian artificial intelligence and robotics Diagnosis Engineering

来源：评论

学校读者我要写书评

暂无评论

Predictive Analysis For Cloud Infrastructure Metrics

Predictive Analysis For Cloud Infrastructure Metrics

引用

作者： Paridhi Agrawal San Jose State University

学位级别：硕士

In a cloud computing environment, enterprises have the flexibility to request resources according to their application demands. This elastic feature of cloud computing makes it an attractive option for enterprises to host their applications on the cloud. Cloud providers usually exploit this elasticity by auto-scaling the application resources for quality assurance. However, there is a setup-time delay that may take minutes between the demand for a new resource and it being prepared for utilization. This causes the static resource provisioning techniques, which request allocation of a new resource only when the application breaches a specific threshold, to be slow and inefficient for the resource allocation task. To overcome this limitation, it is important to foresee the upcoming resource demand for an application before it becomes overloaded and trigger resource allocation in advance to allow setup time for the newly allocated resource. Machine learning techniques like time-series forecasting can be leveraged to provide promising results for dynamic resource allocation. In this research project, I developed a predictive analysis model for dynamic resource provisioning for cloud infrastructure. The researched solution demonstrates that it can predict the upcoming workload for various cloud infrastructure metrics upto 4 hours in future to allow allocation of virtual machines in advance.

关键词： Cloud computing time-series analytics resource allocation artificial intelligence and robotics Databases and Information Systems OS and Networks

来源：评论

学校读者我要写书评

暂无评论

Chatbots With Personality Using Deep Learning

Chatbots With Personality Using Deep Learning

引用

作者： Susmit Gaikwad San Jose State University

学位级别：硕士

Natural Language Processing (NLP) requires the computational modelling of the complex relationships of the syntax and semantics of a language. While traditional machine learning methods are used to solve NLP problems, they cannot imitate the human ability for language comprehension. With the growth in deep learning, these complexities within NLP are easier to model, and be used to build many computer applications. A particular example of this is a chatbot, where a human user has a conversation with a computer program, that generates responses based on the userâs input. In this project, we study the methods used in building chatbots, what they lack and what can be improved.

关键词： Chatbots deep learning natural language processing neural networks artificial intelligence and robotics Other Computer Sciences

来源：评论

学校读者我要写书评

暂无评论

Deep Learning For Image Spam Detection

Deep Learning For Image Spam Detection

引用

作者： Tazmina Sharmin San Jose State University

学位级别：硕士

Spam can be defined as unsolicited bulk email. In an effort to evade text-based spam filters, spammers can embed their spam text in an image, which is referred to as image spam. In this research, we consider the problem of image spam detection, based on image analysis. We apply various machine learning and deep learning techniques to real-world image spam datasets, and to a challenge image spam-like dataset. We obtain results comparable to previous work for the real-world datasets, while our deep learning approach yields the best results to date for the challenge dataset.

关键词： image spam deep learning artificial intelligence and robotics Information Security

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12页 << < 3 4 5 6 7 8 9 10 11 12 > >>

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：