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

7,090 篇 会议
47 篇 期刊文献
39 册 图书

馆藏范围

7,176 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

4,912 篇 工学
- 4,098 篇 计算机科学与技术...
- 2,520 篇 软件工程
- 1,048 篇 信息与通信工程
- 789 篇 控制科学与工程
- 663 篇 生物工程
- 642 篇 电气工程
- 424 篇 生物医学工程（可授...
- 285 篇 交通运输工程
- 281 篇 机械工程
- 226 篇 仪器科学与技术
- 226 篇 安全科学与工程
- 206 篇 建筑学
- 197 篇 动力工程及工程热...
- 185 篇 光学工程
- 166 篇 化学工程与技术
- 154 篇 土木工程
1,899 篇 理学
- 1,065 篇 数学
- 717 篇 生物学
- 442 篇 统计学（可授理学、...
- 285 篇 物理学
- 252 篇 系统科学
- 140 篇 化学
1,151 篇 管理学
- 655 篇 管理科学与工程(可...
- 582 篇 图书情报与档案管...
- 315 篇 工商管理
407 篇 医学
- 353 篇 临床医学
- 297 篇 基础医学(可授医学...
- 188 篇 药学(可授医学、理...
244 篇 教育学
- 243 篇 教育学
211 篇 法学
- 197 篇 社会学
119 篇 农学
111 篇 经济学
50 篇 文学
7 篇 艺术学
5 篇 军事学

主题

557 篇 machine learning
456 篇 deep learning
269 篇 training
253 篇 data mining
240 篇 data models
220 篇 feature extracti...
218 篇 accuracy
184 篇 support vector m...
178 篇 predictive model...
138 篇 neural networks
137 篇 machine learning...
133 篇 computational mo...
131 篇 reinforcement le...
108 篇 convolutional ne...
103 篇 real-time system...
92 篇 forecasting
90 篇 artificial intel...
89 篇 learning systems
88 篇 transfer learnin...
86 篇 big data

机构

69 篇 chitkara univers...
17 篇 school of electr...
15 篇 computer science...
14 篇 harbin engineeri...
13 篇 graphic era hill...
12 篇 building civil a...
12 篇 uttaranchal inst...
12 篇 computer science...
11 篇 university of ch...
10 篇 school of electr...
10 篇 school of comput...
10 篇 graphic era deem...
10 篇 school of electr...
10 篇 yonsei univ dept...
9 篇 wuhan university...
9 篇 univ chinese aca...
9 篇 school of inform...
8 篇 school of remote...
7 篇 university of sa...
7 篇 microsoft resear...

作者

17 篇 kukreja vinay
15 篇 vinay kukreja
13 篇 yin hujun
12 篇 liu yang
12 篇 corchado emilio
11 篇 mehta shiva
10 篇 shiva mehta
10 篇 hujun yin
10 篇 cho sung-bae
9 篇 notsu akira
9 篇 silva catarina
9 篇 alhajj reda
7 篇 ksieniewicz pawe...
7 篇 hammer barbara
7 篇 zhang byoung-tak
7 篇 wozniak michal
7 篇 hussain abir
7 篇 soubra hassan
7 篇 huang de-shuang
7 篇 camacho david

语言

6,194 篇 英文
971 篇 其他
31 篇 中文
1 篇 西班牙文
1 篇 俄文

检索条件"任意字段=11th International Conference on Intelligent Data Engineering and Automated Learning"

共 7176 条记录，以下是4181-4190 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：

Development of a Cloud-based Computational Framework for an Empathetic Robot 2019

Development of a Cloud-based Computational Framework for an ...

引用

11th international conference on Computer and Automation engineering (ICCAE)

作者： Salaken, Syed Moshfeq Nahavandi, Saeid McGinn, Conor Hossny, Mohammed Kelly, Kevin Abobakr, Ahmed Nahavandi, Darius Iskander, Julie Deakin Univ Geelong Vic Australia Trinity Coll Dublin Dublin Ireland

ISBN: (纸本)9781450362870

this article presents the development and preliminary evaluation of an empathy controlled robot. Such a robot is one step forward towards industry 5.0, as it provides a theoretical framework to enable the performance of the robot to be customized to suit the needs of both the task as well as the operator. An inventive step is taken through the separation of computational resources based on whether the algorithms are addressing functional or experiential needs. the paper therefore addresses the requirement for new approaches that can be employed in the design of mobile robots to reduce cost, power consumption, and computational burden of the system. We propose that tasks requiring real-time and safety critical control are processed using dedicated on-board computers, whereas functionality dedicated to system optimization, machine learning and customization are handled through use a cloud-based platform. In this paper, key components of the architecture are defined, and the development and preliminary evaluation of an exemplar robot capable of changing its behavior in accordance with the perceived emotional state of an operator's voice is presented.

关键词： emotion classification robot deep learning cloud control intent perception

来源：评论

学校读者我要写书评

暂无评论

Transfer learning with Res2Net for Remote Sensing Scene Classification

Transfer Learning with Res2Net for Remote Sensing Scene Clas...

引用

international conference on Confluence the Next Generation Information Technology Summit (Confluence)

作者： Arijit Das Saravanan Chandran Tata Consultancy Services Limited Kolkata India National Institute of Technology Durgapur India

ISBN: (数字)9781665414517

ISBN: (纸本)9781665430340

Remote sensing is the method of obtaining data of a particular geographic region of interest with the help of sensors. Often, this data is in form of images, and analyzing such images can give useful information that can help mankind in several ways. In recent years, several methods have been proposed for the same purpose. Most of the successful ones are based on deep learning. Deep learning architectures have a large number of randomly-initialized weights (or parameters) that are trained to extract features from images. Often these weights fail to fully train due to a lack of proper and sufficient training data. To address this issue, transfer learning was introduced. Transfer learning is a technique inspired by humans, which involves initializing deep learning models with weights pretrained on a separate task and fine-tuning them further by training on the desired data. In this work, the same technique is used for classifying remote sensing scenes, with a newly found novel architecture called Res2Net. A single Res2Net block extracts multi-scale features from the input using several receptive layers hierarchically connected to each other with residual-like connections. Although this technique slightly increases the total number of weights, it is capable of capturing relevant and complex features at a granular level. the performance of the proposed approach is evaluated on three remote sensing datasets - UC Merced, Brazilian Coffee Scenes, and EuroSAT dataset and classification accuracies of 98.76%, 93.25%, and 97.50% are achieved, respectively. the method is tested with two fine-tuning techniques on different variations of Res2Net-50. Comparisons with other recently proposed methodologies are shown and confusion matrices are further plotted to better understand the classification potential. the PyTorch code for this work is available at https://***/iamarijit/res2net-remote-sense.

关键词： Deep learning Training Image analysis Transfer learning Training data Feature extraction Remote sensing

来源：评论

学校读者我要写书评

暂无评论

Active learning and User Segmentation for the Cold-start Problem in Recommendation Systems 11

Active Learning and User Segmentation for the Cold-start Pro...

引用

11th international Joint conference on Knowledge Discovery, Knowledge engineering and Knowledge Management (IC3K) / 11th international conference on Knowledge Discovery and Information Retrieval (KDIR)

作者： Alabdulrahman, Rabaa Viktor, Herna Paquet, Eric Univ Ottawa Sch Elect Engn & Comp Sci Ottawa ON Canada Natl Res Council Canada Ottawa ON Canada

ISBN: (纸本)9789897583827

Recommendation systems, which are employed to mitigate the information overload faced by e-commerce users, have succeeded in aiding customers during their online shopping experience. However, to be able to make accurate recommendations, these systems require information about the items for sale and information about users' individual preferences. Making recommendations to new customers, with no prior data in the system, is therefore challenging. this scenario, called the "cold-start problem," hinders the accuracy of recommendations made to a new user. In this paper, we introduce the popular users personalized predictions (PUPP) framework to address cold-starts. In this framework, soft clustering and active learning is used to accurately recommend items to new users. Experimental evaluation shows that the PUPP framework results in high performance and accurate predictions. Further, focusing on frequent, or so-called "popular," users during our active-learning stage clearly benefits the learning process.

关键词： Recommendation Systems Collaborative Filtering Cold-start Active learning

来源：评论

学校读者我要写书评

暂无评论

Sentence Selective Neural Extractive Summarization with Reinforcement learning 11

Sentence Selective Neural Extractive Summarization with Rein...

引用

11th international conference on Knowledge and Systems engineering (KSE)

作者： Chen, Laifu Minh Le Nguyen Japan Adv Inst Sci & Technol Sch Informat Sci Nomi Ishikawa Japan

ISBN: (纸本)9781728130033

In this work we employed a common Recurrent Neural Network (RNN) based sequence model for single document summarization, composed of encoder-extractor hierarchical network architecture. We develop a sentence level selective encoding mechanism to select important feature before extracting sentences, and use a novel reinforcement learning based training algorithm to extend the sequence model. Besides, for single document extractive summarization task, most of researchers only pay attention to the main part of document. We analyze and explore the side information such as the headline and image caption in both CNN and Daily Mail news datasets. Empirical experiment results show the effect that our model outperforms the baseline model, and can be comparable with the state-of-the-art extractive systems when automatically evaluated in the ROUGE metric. the statistics analysis of the data set verifies our experiment results.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Ontological Integration of Semantics and Domain Knowledge in Energy Scenario Co-simulation 11

Ontological Integration of Semantics and Domain Knowledge in...

引用

11th international Joint conference on Knowledge Discovery, Knowledge engineering and Knowledge Management (IC3K) / 11th international conference on Knowledge engineering and Ontology Development (KEOD)

作者： Schwarz, Jan Lehnhoff, Sebastian Carl von Ossietzky Univ Oldenburg Dept Comp Sci Oldenburg Germany

ISBN: (纸本)9789897583827

the transition of the power system to more decentralized power plants and intelligent devices in a smart grid leads to a significant rise in complexity. For testing new technologies before their implementation in the field co-simulation is an important approach, which allows to couple diverse simulation models from different domains. In the planning and evaluation of co-simulation scenarios experts from different domains have to collaborate. To assist the stakeholder in this process, we propose to integrate on the one hand semantics of simulation models and exchanged data and on the other hand domain knowledge in the planning, execution, and evaluation of interdisciplinary co-simulation based on ontologies. this approach aims to allow the high-level planning of simulation and the seamless integration of its information to simulation scenario specification, execution and evaluation. thus, our approach intents to improve the usability of large-scale interdisciplinary co-simulation scenarios.

关键词： Co-simulation data Management Energy Scenarios Information Model Ontology Sustainability

来源：评论

学校读者我要写书评

暂无评论

Multivariate Time Series Forecasting with Deep learning Proceedings in Energy Consumption 11

Multivariate Time Series Forecasting with Deep Learning Proc...

引用

作者： Mellouli, Nedra Akerma, Mahdjouba Minh Hoang Leducq, Denis Delahaye, Anthony Univ Paris 08 LIASD EA4383 IUT Montreuil Vincennes St Denis France Irstea UR GPAN Antony France

ISBN: (纸本)9789897583827

We propose to study the dynamic behavior of indoor temperature and energy consumption in a cold room during demand response periods. Demand response is a method that consists of smoothing demand over time, seeking to reduce or even stop consumption during periods of high demand in order to shift it to periods of lower demand. Such a system can therefore be tackled as the study of a time-series, where each behavioral parameter is a time-varying parameter. Different network topologies are considered, as well as existing approaches for solving multi-step ahead prediction problems. the predictive performance of short-term predictors is also examined with regard to prediction horizon. the performance of the predictors are evaluated using measured data from real scale buildings, showing promising results for the development of accurate prediction tools.

关键词： Demand Response Deep learning Time Series Forecasting

来源：评论

学校读者我要写书评

暂无评论

Feature Selection for Anomaly Detection in Call Center data 11

Feature Selection for Anomaly Detection in Call Center Data

引用

11th international conference on Electrical and Electronics engineering (ELECO)

作者： Iheme, Leonardo O. Ozan, Sukru AdresGezgini Inc Res & Dev Ctr Izmir Turkey

ISBN: (纸本)9786050112757

In this study, we present the process of designing machine learning models for the detection of call center agent malpractices. Based on the features extracted from audio recordings of a given telephone conversation, appropriate one-class support vector machine, isolation forest, and multivariate Gaussian models are trained, evaluated and compared in order to determine the best use case. the labeled data used in the experiments was obtained from a real call center and the results obtained indicate that the system is usable in a real-world scenario. the accuracy of used machine learning models are validated by using the F1 score as a metric.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Application of Mixtures of Gaussians for Tracking Clusters in Spatio-temporal data 11

Application of Mixtures of Gaussians for Tracking Clusters i...

引用

作者： Ertl, Benjamin Meyer, Joerg Streit, Achim Schneider, Matthias Karlsruhe Inst Technol KIT Steinbuch Ctr Comp SCC Karlsruhe Germany Karlsruhe Inst Technol KIT Inst Meteorol & Climate Res IMK ASF Karlsruhe Germany

ISBN: (纸本)9789897583827

Clustering data based on their spatial and temporal similarity has become a research area with increasing popularity in the field of data mining and data analysis. However, most clustering models for spatio-temporal data introduce additional complexity to the clustering process as well as scalability becomes a significant issue for the analysis. this article proposes a data-driven approach for tracking clusters with changing properties over time and space. the proposed method extracts cluster features based on Gaussian mixture models and tracks their spatial and temporal changes without incorporating them into the clustering process. this approach allows the application of different methods for comparing and tracking similar and changing cluster properties. We provide verification and runtime analysis on a synthetic dataset and experimental evaluation on a climatology dataset of satellite observations demonstrating a performant method to track clusters with changing spatio-temporal features.

关键词： Machine learning Pattern Recognition Clustering Spatio-temporal data Mixtures of Gaussians Climate Research

来源：评论

学校读者我要写书评

暂无评论

6th international Workshop on Security of Industrial Control Systems and Cyber-Physical Systems, CyberICPS 2020, 2nd international Workshop on Security and Privacy Requirements engineering, SECPRE 2020, and 3rd international Workshop on Attacks and Defenses for Internet-of-things, ADIoT 2020, held in conjunction with 25th European Symposium on Research in Computer Security, ESORICS 2020

6th International Workshop on Security of Industrial Control...

引用

6th international Workshop on Security of Industrial Control Systems and Cyber-Physical Systems, CyberICPS 2020, 2nd international Workshop on Security and Privacy Requirements engineering, SECPRE 2020, and 3rd international Workshop on Attacks and Defenses for Internet-of-things, ADIoT 2020, held in conjunction with 25th European Symposium on Research in Computer Security, ESORICS 2020

ISBN: (纸本)9783030643294

the proceedings contain 16 papers. the special focus in this conference is on Security of Industrial Control Systems and Cyber-Physical Systems. the topics include: Integrated Analysis of Safety and Security Hazards in Automotive Systems;GDPR Compliance: Proposed Guidelines for Cloud-Based Health Organizations;aligning the Concepts of Risk, Security and Privacy Towards the Design of Secure intelligent Transport Systems;identifying Implicit Vulnerabilities through Personas as Goal Models;Cooperative Speed Estimation of an RF Jammer in Wireless Vehicular Networks;extended Abstract: Towards Physical-Layer Authentication for Backscatter Devices;p2Onto: Making Privacy Policies Transparent;extended Abstract - Transformers: Intrusion Detection data in Disguise;attack Path Analysis for Cyber Physical Systems;identifying and Analyzing Implicit Interactions in a Wastewater Dechlorination System;a Survey of Cryptography-Based Authentication for Smart Grid Communication;cybersecurity Awareness Platform with Virtual Coach and automated Challenge Assessment;ioT Vulnerability Scanning: A State of the Art;learning from Vulnerabilities - Categorising, Understanding and Detecting Weaknesses in Industrial Control Systems;self Adaptive Privacy in Cloud Computing Environments: Identifying the Major Socio-Technical Concepts;definition and Verification of Security Configurations of Cyber-Physical Systems.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Active dataset Generation for Meta-learning System Quality Improvement 20th

Active Dataset Generation for Meta-learning System Quality I...

引用

20th international conference on intelligent data engineering and automated learning (IDEAL)

作者： Zabashta, Alexey Filchenkov, Andrey ITMO Univ Machine Learning Lab 49 Kronverksky Pr St Petersburg 197101 Russia

ISBN: (纸本)9783030336073;9783030336066

Meta-learning use meta-features to formally describe datasets and find possible dependencies of algorithm performance from them. But there is not enough of various datasets to fill a meta-feature space with acceptable density for future algorithm performance prediction. To solve this problem we can use active learning. But it is required ability to generate nontrivial datasets that can help to improve the quality of the meta-learning system. In this paper we experimentally compare several such approaches based on maximize diversity and Bayesian optimization.

关键词： Machine learning Meta-learning Active learning Evolutionary Computation Optimization

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500页 << < 415 416 417 418 419 420 421 422 423 424 > >>

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：