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

101 篇 会议

馆藏范围

101 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

65 篇 工学
- 62 篇 计算机科学与技术...
- 18 篇 信息与通信工程
- 17 篇 电气工程
- 16 篇 控制科学与工程
- 16 篇 交通运输工程
- 15 篇 网络空间安全
- 13 篇 仪器科学与技术
- 13 篇 动力工程及工程热...
- 13 篇 安全科学与工程
- 6 篇 软件工程
- 3 篇 生物工程
- 2 篇 电子科学与技术（可...
- 2 篇 生物医学工程（可授...
- 1 篇 机械工程
- 1 篇 光学工程
- 1 篇 材料科学与工程（可...
20 篇 管理学
- 18 篇 管理科学与工程(可...
- 15 篇 图书情报与档案管...
- 2 篇 工商管理
18 篇 理学
- 13 篇 化学
- 4 篇 数学
- 3 篇 生物学
- 2 篇 统计学（可授理学、...
- 1 篇 系统科学
5 篇 教育学
- 5 篇 教育学
1 篇 法学
- 1 篇 社会学

主题

22 篇 deep learning
14 篇 machine learning
12 篇 data models
10 篇 training data
8 篇 smart cities
7 篇 data mining
7 篇 feature extracti...
6 篇 training
5 篇 object detection
5 篇 roads
5 篇 neural networks
5 篇 predictive model...
5 篇 federated learni...
5 篇 data augmentatio...
4 篇 task analysis
4 篇 image segmentati...
4 篇 computational mo...
4 篇 semantics
3 篇 natural language...
3 篇 energy consumpti...

机构

2 篇 graduate school ...
2 篇 univ monastir la...
2 篇 univ minho algor...
2 篇 univ moncton dep...
2 篇 ccg zgdv inst ep...
1 篇 key laboratory o...
1 篇 univ quebec dept...
1 篇 national institu...
1 篇 univ waterloo wa...
1 篇 graduate school ...
1 篇 college of infor...
1 篇 college of big d...
1 篇 faculty of trans...
1 篇 graduate school ...
1 篇 handong global u...
1 篇 univ monastir hi...
1 篇 school of inform...
1 篇 norwegian univer...
1 篇 school of big da...
1 篇 univ oxford dept...

作者

3 篇 novais paulo
3 篇 hammer barbara
2 篇 ben abdallah asm...
2 篇 cortez paulo
2 篇 hiroharu kawanak...
2 篇 tadanori fukami
2 篇 chen nan
2 篇 horvath tomas
2 篇 launet laetitia
2 篇 akhloufi moulay ...
2 篇 yang ruiqi
2 篇 colomer adrian
2 篇 pilastri andre
2 篇 bedoui mohamed h...
2 篇 zhang yue
2 篇 naranjo valery
2 篇 matos luis migue...
2 篇 dai qinling
2 篇 faria hugo
1 篇 karras aristeidi...

语言

100 篇 英文
1 篇 其他
1 篇 中文

检索条件"任意字段=23rd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2022"

共 101 条记录，以下是71-80 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：

Ball Trapping in the Simulated Soccer using Decision Tree based learning to Rank

Ball Trapping in the Simulated Soccer using Decision Tree ba...

引用

international Symposium on Soft Computing and intelligent Systems (SCIS)

作者： Hidehisa Akiyama Department of Information Science and Engineering Okayama University of Science Okayama Japan

In a group ball game such as soccer, the ball passing behavior between players is important for achieving cooperative team behavior. To acquire the ball passing behavior, conventional approaches mainly apply search and machine learning to the decision making of the players who perform the passing action. On the other hand, the position and posture of the pass receiver player when receiving the ball have not been studied sufficiently. This paper proposes a machine learning method using decision tree based learning to rank to select a more advantageous ball trapping behavior. We use the RoboCup Soccer Simulator as an experimental environment to collect training datasets and to evaluate the performance of the action selection model.

关键词： Training Training data Games Receivers Behavioral sciences Numerical models Decision trees

来源：评论

学校读者我要写书评

暂无评论

Design of Federated learning Engagement Method for Autonomous Vehicle Privacy Protection

Design of Federated Learning Engagement Method for Autonomou...

引用

international Symposium on Soft Computing and intelligent Systems (SCIS)

作者： Jung-Sook Kim School of Contents and Design Kimpo University Gimpo-si Geyonggi-do Korea

An autonomous car is defined as a vehicle that can be operated only by an autonomous driving system and does not require a driver or intervention of a driver or passenger. Various types of data collected for fully autonomous car operation include personal information such as location, image, physical, behavior information, and license number. It is hard for a driver or pedestrian to recognize or control automated collection and processing of personal information by autonomous vehicles in real time. It is, therefore, necessary to prepare and apply appropriate countermeasures such as minimizing the collection of personal information, deleting and encrypting unnecessary information, etc. Federated learning is a distributed machine learning technique that can learn Al models in cooperation with each other without directly sharing data distributed and stored in multiple locations, such as devices or institutions. Instead of transmitting individual client data to the central server (cloud), the Al model of the central server is sent to the client to train the model with each data. By repeating this process, the global Al model of the central server becomes more general and the accuracy of the local Al model of the client improves. In order to protect personal information collected while driving an autonomous car, this paper proposed a federated learning engagement method, where cross-device was used to engage in the federated learning consisting of a very large number of mobile devices, and based on this, personal information can be protected for the efficient operation of autonomous vehicles.

关键词： Privacy Federated learning Process control data models Real-time systems Mobile handsets Servers

来源：评论

学校读者我要写书评

暂无评论

Application of machine learning models for partial remote work intension in provincial areas of Japan

Application of machine learning models for partial remote wo...

引用

international Symposium on Soft Computing and intelligent Systems (SCIS)

作者： Masashi Okushima Dept. of civil and environmental engineering Tokushima University Tokushima Japan

The purpose of this study is to model the relationship between the intention of remote work and its factors in the provincial areas of Japan. Particularly, we focus on partial remote work, which is easy to implement. Therefore, using remote work intention data, we construct not only regular remote work models but also partial remote work models. On these models, we applied various machine learning models to compare the learning accuracy. As a result, we found shopping time as a crucial factor in regular remote work. we also showed working hours as a key factor in partial remote work. The decision tree model has the same or higher estimation accuracy with fewer variables than the logistic regression model. The random forest model and the SVM model were able to train accurately for learning data. Regarding the verification of remote work, there was no significant difference in each modeling.

关键词： Support vector machines Estimation data models Regression tree analysis Random forests Logistics

来源：评论

学校读者我要写书评

暂无评论

A spiking neural network that extracts frequent symbol patterns from time-series data with different symbol appearance intervals

A spiking neural network that extracts frequent symbol patte...

引用

international Symposium on Soft Computing and intelligent Systems (SCIS)

作者： Kenta Morita Naoki Morita Faculty of Medical Engineering Suzuka university of medical science Mie Japan School of Information Telecommunication Engineering Tokai University Tokyo Japan

In this research, we aim to extract frequent symbol patterns from symbol sequences. In the target time series data, the appearance timing of symbols is different. The purpose is to absorb the deviation of the appearance timing and extract frequent symbol patterns. This paper proposes a spiking neural network that extracts frequent symbol patterns. The structure of the proposed network grows automatically each time a symbol is given. By learning the network, the output unit will only fire when given a frequent symbol pattern, and the network will extract the frequent symbol patterns. As a result of a simple experiment, it was confirmed that the proposed network can extract frequent symbol patterns from the target time series data.

关键词： Time series analysis Neural networks Symbols Timing data mining Task analysis Videos

来源：评论

学校读者我要写书评

暂无评论

Effects of Accuracy-based Single-Objective Optimization in Multiobjective Fuzzy Genetics-based Machine learning

Effects of Accuracy-based Single-Objective Optimization in M...

引用

international Symposium on Soft Computing and intelligent Systems (SCIS)

作者： Takeru Konishi Naoki Masuyama Yusuke Nojima School of Engineering Osaka Prefecture University Sakai Japan Graduate School of Informatics Osaka Metropolitan University Sakai Japan

Fuzzy classifier design often requires the maximization of classification accuracy and minimization of model complexity. Multiobjective Fuzzy Genetics-Based Machine learning (MoFGBML) can efficiently obtain a set of fuzzy classifiers considering the above-mentioned two objectives simultaneously using an evolutionary multiobjective optimization algorithm. However, the search by MoFGBML is biased toward minimizing the complexity, and it is easy to obtain classifiers with low complexity. At the same time, it is difficult to obtain classifiers with high classification accuracy. In this paper, we propose a two-stage MoFGBML, which first performs accuracy-oriented single-objective optimization to obtain a set of accurate classifiers with a large number of rules. Then, multiobjective optimization is performed to obtain a wide variety of classifiers, from highly-accurate ones to very simple ones.

关键词： Machine learning algorithms Error analysis Training data Machine learning Minimization Genetics Complexity theory

来源：评论

学校读者我要写书评

暂无评论

Tool Diagnosis Method of CNC Machine based on Color Space Conversion and Deep learning

Tool Diagnosis Method of CNC Machine based on Color Space Co...

引用

international Symposium on Soft Computing and intelligent Systems (SCIS)

作者： Eun Kyeong Kim Seunghwan Jung Minseok Kim Jin Yong Kim Baekcheon Kim Sungshin Kim dept. of Electrical and Electronics Engineering Pusan National University Busan Korea dept. of Electrical Engineering Pusan National University Busan Korea

Tool diagnosis system is necessary to prevent an accident or defective product. This paper proposes the tool diagnosis method of CNC machines based on color space conversion and deep learning. To apply the deep learning algorithm, we generated images from the current data of CNC machines by wavelet transform. However, generated images by wavelet transform are difficult to distinguish whether it is normal data image or not. Because generated images by wavelet transform are very similar and there is no outstanding feature. Therefore, we applied color space conversion from RGB image to CIE L*a*b* image. Converted images represent outstanding features whereas generated images by wavelet transform and RGB images do not. And, to make up for imbalanced data, oversampling is applied. Finally, deep learning algorithm is trained to classify the converted images. Experimental results showed that the proposed method can implement the deep learning network for tool diagnosis of CNC machine effectively.

关键词： Wavelet transforms Deep learning Training Image color analysis Wavelet analysis Classification algorithms Matrix converters

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of a Multicellular Molecular Communication Simulator

Design and Implementation of a Multicellular Molecular Commu...

引用

international Symposium on Soft Computing and intelligent Systems (SCIS)

作者： Takanori Saiki Tadashi Nakano Department of Electrical and Information Engineering Osaka City University Japan Graduate School of Informatics Osaka Metropolitan University Japan

This paper describes the design and implementation of an extensible and fast simulation platform for multicellular molecular communication simulations. The simulation platform is extensible, allowing users to customize the cell mechanics model and conduct their own simulation experiments. The simulation platform is built upon efficient algorithms and supports large-scale simulations. This paper presents its initial design and current implementation status. An example simulation run using the standard simulation model is shown, demonstrating the potential use of the simulation platform to conduct biologically realistic simulation experiments.

关键词： Analytical models Biological system modeling Machine learning Mathematical models data models Molecular communication (telecommunication) Standards

来源：评论

学校读者我要写书评

暂无评论

Adversarial Ensemble Modeling for Evasion Attack Detection

Adversarial Ensemble Modeling for Evasion Attack Detection

引用

international Symposium on Soft Computing and intelligent Systems (SCIS)

作者： Usman Ahmed Jerry Chun-Wei Lin Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Bergen Norway

This article presents a hybrid method that statically evaluates several aspects regarding network-based model, text, as well as permissions, and monitors several activities dynamically; those activities include system call logs, memory usage, as well as the CPU usage. Thus, the designed machine learning-based model can easily distinguished, as well as identify Android ransomware among different and varied types of malware. According to the results, the machine learning-based approach proposed for Android ransomware classification and detection is able to classify unknown malware that exhibits the same static and dynamic behavior; it can prevent adversarial evasion attacks. Moreover, it was found that the data from permissions and system calls are more valuable to detect ransomware. These features and other considered static and dynamic features detect and classify Android Ransomware with high accuracy.

关键词： Uniform resource locators Machine learning Feature extraction Electronic mail Behavioral sciences Ransomware Object recognition

来源：评论

学校读者我要写书评

暂无评论

Quantifying and Debiasing Gender Bias in Japanese Gender-specific Words with Word Embedding

Quantifying and Debiasing Gender Bias in Japanese Gender-spe...

引用

international Symposium on Soft Computing and intelligent Systems (SCIS)

作者： Leisi Chen Toru Sugimoto Graduate School of Engineering and Science Shibaura Institute of Technology Tokyo Japan Faculty of Engineering Shibaura Institute of Technology Tokyo Japan

Machine learning is playing a significant role in modern life. However, the problem that Machine learning has biases and stereotypes has also drawn the researcher's attention. Word2Vec, a popular framework in the NLP field to encode the word's meaning as a real-valued vector, has been used in many machine learning and natural language processing tasks. Still, it also has been proved that it contains severe biases toward women. In this paper, we used Word2Vec to analyze the relationship between gender-specific words and personality adjectives in Japanese to Figure out the latent gender bias in those gender-specific words. We first found that the Word2Vec model trained by Japanese Wikipedia data shows that some occupation gender-specific words strongly connect with negative personality adjectives. The experiment results reflect that people commonly use these gender-specific words to criticize women in these specific occupations. Then we eliminated the projection of word vectors of personality adjectives on the gender subspace and reduced the relationship between negative personality adjectives and gender-specific words by word vector calculation.

关键词： Machine learning algorithms Machine learning Encyclopedias Natural language processing data models Internet Online services

来源：评论

学校读者我要写书评

暂无评论

Adaptation to a brain-computer interface of transfer learning using event-related potentials obtained under different measurement conditions

Adaptation to a brain-computer interface of transfer learnin...

引用

international Symposium on Soft Computing and intelligent Systems (SCIS)

作者： Hikaru Sato Aoi Yoshida Bunnoshin Ishikawa Tadanori Fukami Graduate School of Science and Engineering Yamagata University Yonezawa Japan Department of Psychiatry Hotokukai Utsunomiya Hospital Utsunomiya Japan

Event-related potentials (ERPs) are widely used in electroencephalogram (EEG)-based brain-computer interfaces (BCIs). Because ERPs vary with age, individual differences, and task difficulty, identifying useful features is challenging. In recent years, deep learning, in which features can be acquired via learning, has been used to identify such features. However, a large amount of BCI data is required for deep learning, and data collection can be difficult. Therefore, we attempted to verify the applicability of BCI to transfer learning based on a considerable amount of data obtained from clinical examinations. The components of an ERP vary depending on measurement conditions; therefore, they degrade the performance of transfer learning. Thus, we proposed to improve performance using latency correction to shift waveforms along the time axis. We trained EEGNet with 5600 responses obtained from a clinical auditory oddball paradigm. In the BCI experiment, 12 subjects input one of the four characters presented on a display. The use of deep learning resulted in an approximately 10% higher performance than the conventional method based on the P300 amplitude. Furthermore, an improvement of approximately 5% in accuracy was observed when latency correction was used.

关键词： Deep learning Electric potential Transfer learning Estimation data collection Brain-computer interfaces Task 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11页 << < 2 3 4 5 6 7 8 9 10 11 > >>

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：