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

1,730 篇 会议
45 册 图书
11 篇 期刊文献

馆藏范围

1,785 篇 电子文献
1 种 纸本馆藏

日期分布

学科分类号

1,223 篇 工学
- 1,093 篇 计算机科学与技术...
- 628 篇 软件工程
- 254 篇 信息与通信工程
- 199 篇 电气工程
- 177 篇 生物工程
- 99 篇 控制科学与工程
- 98 篇 生物医学工程（可授...
- 60 篇 光学工程
- 46 篇 化学工程与技术
- 45 篇 电子科学与技术（可...
- 41 篇 机械工程
- 40 篇 仪器科学与技术
- 40 篇 安全科学与工程
- 29 篇 交通运输工程
- 28 篇 动力工程及工程热...
- 27 篇 材料科学与工程（可...
455 篇 理学
- 199 篇 数学
- 196 篇 生物学
- 144 篇 物理学
- 83 篇 统计学（可授理学、...
- 51 篇 系统科学
- 45 篇 化学
233 篇 管理学
- 167 篇 图书情报与档案管...
- 86 篇 管理科学与工程(可...
- 43 篇 工商管理
182 篇 医学
- 160 篇 临床医学
- 72 篇 基础医学(可授医学...
- 39 篇 药学(可授医学、理...
- 32 篇 公共卫生与预防医...
34 篇 法学
- 30 篇 社会学
17 篇 经济学
14 篇 教育学
11 篇 农学
2 篇 艺术学
1 篇 军事学

主题

239 篇 machine learning
184 篇 deep learning
140 篇 pattern recognit...
110 篇 feature extracti...
91 篇 support vector m...
88 篇 data mining
79 篇 accuracy
75 篇 training
59 篇 convolutional ne...
51 篇 machine learning...
48 篇 data models
46 篇 artificial intel...
41 篇 computational mo...
40 篇 neural networks
39 篇 face recognition
36 篇 learning systems
36 篇 adversarial mach...
33 篇 predictive model...
32 篇 classification
32 篇 image recognitio...

机构

6 篇 college of compu...
5 篇 xi'an university...
4 篇 badji mokhtar un...
4 篇 shanghai jiao to...
4 篇 institute of big...
4 篇 chitkara centre ...
4 篇 chitkara univers...
4 篇 library shanghai...
3 篇 school of comput...
3 篇 univ chittagong ...
3 篇 chongqing univer...
3 篇 centre of resear...
3 篇 school of comput...
3 篇 school of comput...
3 篇 school of design...
3 篇 korea univ dept ...
3 篇 school of automa...
3 篇 university of mi...
3 篇 shenyang jianzhu...
3 篇 xi'an university...

作者

5 篇 venkatesh svetha
4 篇 ashwini kodipall...
4 篇 zhang yan
4 篇 srinivasa gowri
4 篇 kamel mohamed s.
4 篇 lall brejesh
4 篇 trupthi rao
3 篇 andersson karl
3 篇 peng yang
3 篇 malerba donato
3 篇 karl andersson
3 篇 chaudhury santan...
3 篇 de-shuang huang
3 篇 sekhar c. chandr...
3 篇 wang shuo
3 篇 kamata sei-ichir...
3 篇 mohammad shahada...
3 篇 azizi nabiha
3 篇 phung dinh
3 篇 krasotkina olga

语言

1,587 篇 英文
190 篇 其他
26 篇 中文

检索条件"任意字段=4th International Conference on Machine Learning and Data Minining in Pattern Recognition"

共 1786 条记录，以下是1311-1320 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：

Stream-based active learning in the presence of label noise 4

Stream-based active learning in the presence of label noise

引用

4th international conference on pattern recognition Applications and Methods, ICPRAM 2015

作者： Bouguelia, Mohamed-Rafik Belaïd, Yolande Belaïd, Abdel Université de Lorraine LORIA UMR 7503 Vandoeuvre-les-NancyF-54506 France

ISBN: (纸本)9789897580765

Mislabelling is a critical problem for stream-based active learning methods because it not only impacts the classification accuracy but also deviates the active learner from querying informative data. Dealing with label noise is omitted by most existing active learning methods. We address this issue and propose an efficient method to identify and mitigate mislabelling errors for active learning in the streaming setting. We first propose a mislabelling likelihood measure to characterize the potentially mislabelled instances. this measure is based on the degree of disagreement among the predicted and the queried class label (given by the labeller). then, we derive a measure of informativeness that expresses how much the label of an instance needs to be corrected by an expert labeller. Specifically, an instance is worth relabelling if it shows highly conflicting information among the predicted and the queried labels. We show that filtering instances with a high mislabelling likelihood and correcting only the filtered instances with a high conflicting information greatly improves the performances of the active learner. Experiments on several real world data prove the effectiveness of the proposed method in terms of filtering efficiency and classification accuracy of the stream-based active learner.

关键词： learning systems

来源：评论

学校读者我要写书评

暂无评论

Inducing Awareness for Learners through Visualizing Mutual Evaluation data by a Self-Organizing Map 7

Inducing Awareness for Learners through Visualizing Mutual E...

引用

7th international conference of Soft Computing and pattern recognition (SoCPaR)

作者： Ueki, Yuta Ohnishi, Kei Kyushu Inst Technol Grad Sch Comp Sci & Syst Engn 680-4 Kawazu Iizuka Fukuoka 8208502 Japan

ISBN: (纸本)9781467393607

Self-evaluation and evaluations among peer learners, which together are called mutual evaluations in this study, are presumed to motivate learners to increase learning and introspection. the basis behind these effects is the awareness resulting from the differences between self-evaluation and evaluations from others. therefore, for learners to benefit from the effects of mutual evaluations, we need to easily visualize the mutual evaluation results that make them aware of something. In this paper we design a system to visualize mutual evaluation data, which are many and multi-dimensional data, in such a way that we can easily grasp the overview at first glance and develop an actual system according to the design for fostering "Fundamental Competencies for Working Persons" as an example. In addition, we compare the visualization method used in the developed system with an existing method through a subjective evaluation test and a statistical hypothesis test. Finally, we show the usefulness of our visualization method by comparing the results.

关键词： mutual evaluation visualization awareness self-organizing map

来源：评论

学校读者我要写书评

暂无评论

Modern machine learning techniques and their applications

Modern machine learning techniques and their applications

引用

作者： Ivanović, Mirjana Radovanović, Miloš Department of Mathematics and Informatics Faculty of Sciences University of Novi Sad Novi Sad Serbia

ISBN: (纸本)9781138028302

During the last several decades machine learning (ML) became a mainstay of information technology. One view of ML is that it represents the science of finding patterns and making predictions from data, with the goal of creating systems that learn from experience. ML borders with multivariate statistics, data mining, pattern recognition, and advanced/predictive analytics. Increasing amounts of available data suggest that ML will become an even more pervasive component of technological progress. ML techniques usually belong to one of the main learning styles: supervised, unsupervised, semi-supervised, and reinforcement learning. Relevant methods include decision trees, nearest neighbor techniques, partitional/ hierarchical/density-based clustering, Bayesian approaches, kernel methods, neural networks, and deep learning. the first part of our paper will give an overview of most important ML techniques. We will outline common problems: the bias-variance tradeoff, under/over-fitting, high dimensionality, and big data. the second part will highlight ML applications in business and telecommunications. © 2015 Taylor & Francis Group, London.

关键词： Bayesian networks

来源：评论

学校读者我要写书评

暂无评论

Discriminative kernel feature extraction and learning for object recognition and detection 4

Discriminative kernel feature extraction and learning for ob...

引用

4th international conference on pattern recognition Applications and Methods, ICPRAM 2015

作者： Pan, Hong Olsen, Søren Ingvor Zhu, Yaping Department of Computer Science Univeristy of Copenhagen Copenhagenø2100 Denmark School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9789897580765

Feature extraction and learning is critical for object recognition and detection. By embedding context cue of image attributes into the kernel descriptors, we propose a set of novel kernel descriptors called context kernel descriptors (CKD). the motivation of CKD is to use the spatial consistency of image attributes or features defined within a neighboring region to improve the robustness of descriptor matching in kernel space. For feature learning, we develop a novel codebook learning method, based on the Cauchy-Schwarz Quadratic Mutual Information (CSQMI) measure, to learn a compact and discriminative CKD codebook from a rich and redundant CKD dictionary. Projecting the original full-dimensional CKD onto the codebook, we reduce the dimensionality of CKD without losing its discriminability. CSQMI derived from Rényi quadratic entropy can be efficiently estimated using a Parzen window estimator even in high-dimensional space. In addition, the latent connection between Rényi quadratic entropy and the mapping data in kernel feature space further facilitates us to capture the geometric structure as well as the information about the underlying labels of the CKD using CSQMI. thus the resulting codebook and reduced CKD are discriminative. We report superior performance of our algorithm for object recognition on benchmark datasets like Caltech-101 and CIFAR-10, as well as for detection on a challenging chicken feet dataset.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

learning to predict video saliency using temporal superpixels 4

Learning to predict video saliency using temporal superpixel...

引用

4th international conference on pattern recognition Applications and Methods, ICPRAM 2015

作者： Singh, Anurag Chu, Chee-Hung Henry Pratt, Michael A. Center for Advanced Computer Studies University of Louisiana at Lafayette LafayetteLA United States Informatics Research Institute University of Louisiana at Lafayette LafayetteLA United States W.H. Hall Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA United States

ISBN: (纸本)9789897580772

Visual Saliency of a video sequence can be computed by combining spatial and temporal features that attract a user's attention to a group of pixels. We present a method that computes video saliency by integrating these features: color dissimilarity, objectness measure, motion difference, and boundary score. We use temporal clusters of pixels, or temporal superpixels, to simulate attention associated with a group of moving pixels in a video sequence. the features are combined using weights learned by a linear support vector machine in an online fashion. the temporal linkage for superpixels is then used to find the saliency flow across the image frames. We experimentally demonstrate the efficacy of the proposed method and that the method has better performance when compared to state-of-the-art methods.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

4th international conference on pattern recognition Applications and Methods, ICPRAM 2015

4th International Conference on Pattern Recognition Applicat...

引用

4th international conference on pattern recognition Applications and Methods, ICPRAM 2015

ISBN: (纸本)9783319276762

the proceedings contain 18 papers. the special focus in this conference is on theory and Methods. the topics include: Density difference detection with application to exploratory visualization;identifying and mitigating labelling errors in active learning;a holistic classification optimization framework with feature selection, preprocessing, manifold learning and classifiers;detection of abrupt changes in spatial relationships in video sequences;diffusion-based similarity for image analysis;automatic detection and recognition of symbols and text on the road surface;using BLSTM for spotting regular expressions in handwritten documents;a similarity-based color descriptor for face detection;pose estimation and movement detection for mobility assessment of elderly people in an ambient assisted living application;a non-rigid face tracking method for wide rotation using synthetic data;3-D face recognition using geodesic-map representation and statistical shape modelling;learning discriminative mid-level patches for fast scene classification;modification of polyp size and shape from two endoscope images using RBF neural network;detecting and dismantling composite visualizations in the scientific literature;tensor deep stacking networks and kernel deep convex networks for annotating natural scene images and multi-object segmentation for assisted image reconstruction.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An improvement of non-iterative neural networks for the application of high-dimensional data 4

An improvement of non-iterative neural networks for the appl...

引用

4th international Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2015

作者： Lin, Yu Yoshida, Shinichi Liang, Yanchun School of Software Jilin University Changchun130012 China School of Information Kochi University of Technology Kochi782-8502 Japan

this paper proposes a deep model algorithm combining stacked sparse autoencoder (SSAE) with extreme learning machine (ELM). SSAE with deep model is an approach to automatically learn useful features from unlabeled data. Deep learning has the advantage of learning complicated functions that can represent high-level abstractions. It includes an introduction to the proposed algorithm of Stacked Sparse Autoencoder Extreme learning machine (SSAE-ELM), which is applied into the pattern recognition problems. Moreover, it also contains a strategy based on kernel extreme learning machine (KELM). Finally, it shows that these two combination algorithms have better generalization performance than some other deep architecture network algorithms which took experiments on the same benchmarks. © 2015, Fuji Technology Press Ltd. All rights reserved.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Automated Blog Feedback Prediction with Ada-Boost Classifier 4

Automated Blog Feedback Prediction with Ada-Boost Classifier

引用

4th international conference on Informatics, Electronics & Vision (lCIEV)

作者： Uddin, Md. Taufeeq Int Islamic Univ Chittagong Dept Comp Sci & Engn Chittagong Bangladesh

ISBN: (纸本)9781467369022

Automated analysis of social media documents has a tremendous impact in our day to day life since we extensively use social media to share our thoughts, feelings, tastes etc. However, the automatic social media analysis is still a very challenging task due to the massive amount of social media documents as well as the uncontrolled, dynamic and rapidly-changing content of social media documents. To automate social media analysis, this paper presents an automatic feedback prediction model based on novel Ada-Boost learning algorithm for blog documents considering realistic scenario. In this approach, an Ada-Boost classifier is applied to the numerous features extracted from crawled blog document to predict whether someone comments on a blog document or not in the next 24 hours of its publication in blogs. the evaluation results of the experiments conducted on the publicly available benchmark blog feedback data set indicate that the proposed technique is efficient both in terms of feedback prediction accuracy and computational time;the proposed approach yielded the maximum feedback prediction rate of 91.4%.

关键词： classification document handling electronic publishing feature extraction learning (artificial intelligence) pattern classification social networking (online) AdaBoost classifier AdaBoost learning algorithm automated blog feedback prediction automated social media documents analysis benchmark blog feedback data set blog document computational time feedback prediction accuracy Blogs data mining Feature extraction Media Prediction algorithms Predictive models Training Feature extraction blogs electronic document handling Electronic Publishing Social Media Prediction algorithms computational time pattern recognition Prediction models learning algorithms data mining Functional training Feedback

来源：评论

学校读者我要写书评

暂无评论

4th international Visual Informatics conference, IVIC 2015

4th International Visual Informatics Conference, IVIC 2015

引用

4th international Visual Informatics conference, IVIC 2015

ISBN: (纸本)9783319259383

the proceedings contain 45 papers. the special focus in this conference is on Visualisation, Big data, machine learning and Computer Vision. the topics include: Visual information framework for medical family tree data;determining number of clusters using firefly algorithm with cluster merging for text clustering;design solution for complexities of big data interfaces;fuzzy-based shapelets for mining climate change time series patterns;time series analysis and forecasting of dengue using open data;comparative analysis of different versions of association rule mining algorithm on AWS-EC2;visualisation of trend pattern migrations in social networks;initial user requirement analysis for waterbodies data visualization;developmental analysis of a markerless hybrid tracking technique for mobile augmented reality systems;guideline for designing an effective serious game by using cultural-based game design model;evaluation of wearable device for the elderly;violence recognition using harmonic mean of distances and relational velocity with K-nearest neighbour classifier;familiarity in team-based online games;a membrane computing model for generation of picture arrays;score level fusion scheme in hybrid multibiometric system;a critical comparison of fingerprint fuzzy vault techniques;a comparative study of computer aided system preoperative planning for high tibial osteotomy;a comparison of multi-label feature selection methods using the algorithm adaptation approach;an efficient multi join query optimization for relational database management system using two phase artificial bess colony algorithm;BoVW model for animal recognition;objects contributions towards image annotation and optimized-memory map-reduce algorithm for mobile learning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

learning the Relationship Between Corporate Governance and Company Performance Using data Mining 11th

Learning the Relationship Between Corporate Governance and C...

引用

11th international conference on machine learning and data Mining (MLDM)

作者： Moldovan, Dane Mutu, Simona Univ Babes Bolyai Fac Econ & Business Adm Cluj Napoca 400591 Romania

ISBN: (纸本)9783319210247;9783319210230

the objective of this paper is to identify the relationship between corporate governance variables and firm performance by employing data mining methods. We choose two dependent variables, Tobin's Q ratio and Altman Z-score, as measures for the companies' performances and apply machine learning techniques on the data collected from the components companies of three major stock indexes: S&P 500, STOXX Europe 600 and STOXX Eastern Europe 300. We use decision trees and logistic regressions as learning algorithms, and then we compare their performances. For the US components, we found a positive connection between the presence of women in the board and the company performance, while in Western Europe that it is better to employ a larger audit committee in order to lower the bankruptcy risk. An independent chairperson is a positive factor related to Altman Z-score, for the companies from Eastern Europe.

关键词： machine learning Corporate governance Firm performance Classification Logistic regression Decision Trees

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179页 << < 128 129 130 131 132 133 134 135 136 137 > >>

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：