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

550 篇 会议
28 篇 期刊文献
7 册 图书

馆藏范围

585 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

470 篇 工学
- 425 篇 计算机科学与技术...
- 199 篇 软件工程
- 110 篇 电气工程
- 67 篇 信息与通信工程
- 45 篇 生物工程
- 42 篇 生物医学工程（可授...
- 26 篇 控制科学与工程
- 20 篇 光学工程
- 13 篇 仪器科学与技术
- 11 篇 机械工程
- 10 篇 化学工程与技术
- 9 篇 交通运输工程
- 8 篇 电子科学与技术（可...
- 7 篇 土木工程
140 篇 理学
- 69 篇 数学
- 56 篇 生物学
- 33 篇 物理学
- 24 篇 统计学（可授理学、...
- 19 篇 系统科学
- 8 篇 化学
90 篇 管理学
- 63 篇 图书情报与档案管...
- 35 篇 管理科学与工程(可...
- 19 篇 工商管理
46 篇 医学
- 36 篇 临床医学
- 22 篇 基础医学(可授医学...
- 13 篇 药学(可授医学、理...
- 7 篇 特种医学
- 6 篇 公共卫生与预防医...
11 篇 法学
- 9 篇 社会学
11 篇 教育学
- 10 篇 教育学
8 篇 经济学
6 篇 农学

主题

74 篇 machine learning
55 篇 data mining
36 篇 pattern recognit...
33 篇 deep learning
20 篇 feature extracti...
18 篇 artificial intel...
16 篇 support vector m...
15 篇 learning systems
11 篇 image classifica...
9 篇 training
8 篇 neural networks
8 篇 face recognition
8 篇 manifold learnin...
8 篇 supervised learn...
7 篇 pattern classifi...
7 篇 big data
7 篇 clustering algor...
7 篇 classification (...
7 篇 machine learning...
7 篇 data models

机构

4 篇 ukrainian cathol...
3 篇 harbin inst tech...
3 篇 guilin univ elec...
3 篇 fujian univ tech...
3 篇 college of compu...
3 篇 kunming univ col...
3 篇 nanjing univ sci...
3 篇 concordia univ d...
2 篇 shanghai jiao to...
2 篇 australian e-hea...
2 篇 telangana hydera...
2 篇 key lab data gov...
2 篇 idiap ch-1920 ma...
2 篇 department of ma...
2 篇 univ toronto dep...
2 篇 univ montreal di...
2 篇 chitkara univers...
2 篇 natl univ singap...
2 篇 pattern analysis...
2 篇 univ katolik ind...

作者

3 篇 li junbao
3 篇 maier andreas
3 篇 bengio s
3 篇 deepa r.
3 篇 deng fei
3 篇 pan jeng-shyang
3 篇 hu cong
3 篇 zhang daoqiang
3 篇 amelio alessia
3 篇 maier-hein klaus
3 篇 he chunhui
2 篇 vrahatis aristid...
2 篇 jin zhong
2 篇 collobert r
2 篇 tax dmj
2 篇 sharma r
2 篇 cilia nicole dal...
2 篇 fontanella franc...
2 篇 genov r
2 篇 stiefelhagen rai...

语言

568 篇 英文
12 篇 中文
9 篇 其他
1 篇 俄文

检索条件"任意字段=1st International Workshop on Machine Learning and Data Mining in Pattern Recognition"

共 585 条记录，以下是391-400 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：

The Novel Method About Correlation Calculation Based on An Inequation 24

The Novel Method About Correlation Calculation Based on An I...

引用

1st international Conference on Image Processing machine learning and pattern recognition

作者： Wang, Boyang Deng, Fei Miao, Xisong Yu, Wenjie Zheng, Bowen Kunming Univ Coll Informat Engn Kunming Yunnan Peoples R China Key Lab Data Governance & Intelligent Decis Univ Kunming Yunnan Peoples R China

ISBN: (纸本)9798400707032

Among the many methods of analysing correlation coefficient, the two classical methods are the Spearman correlation coefficient and Pearson correlation coefficient. For the Spearman method, the time complexity is larger because of the sorting data. For the Pearson method, there are also some limited conditions, such as the data are needed to linearly related and continuous, normally distributed or near-normally distributed with a single peak and independent. To avoid the disadvantages about the above correlation coefficients, we propose a novel method about correlation calculation based on an inequation, which derives from inventory model theory and risk pooling theory. Firstly, for the whole dataset, we calculate the sample mean and standard deviation of sub elements and whole datasets respectively. Then, using the inventory model theory, we calculate the total standard deviation of the whole dataset and the sum of standard deviation about sub elements of whole dataset, and obtain the novel inequality. Then, judge this inequality: when "=" is true, conclude that there is no correlation data in the entire dataset X;when ">" is true, it is judged that the entire dataset X has relevant data, furthermore, the bigger the difference of left value subtracts right value, the stronger the correlation. The proposed algorithm owns the lower time complexity and much wider range of uses. Finally, the GDP experiment and Gini index experiment demonstrate the effectiveness of the novel method.

关键词： Novel inequation Correlation calculation Spearman method Pearson method Time complexity Limited condition

来源：评论

学校读者我要写书评

暂无评论

Monitoring network evolution using MDL

Monitoring network evolution using MDL

引用

24th IEEE international Conference on data Engineering/ 1st international workshop on Secure Semantic Web

作者： Ferlez, Jure Faloutsos, Christos Leskovec, Jure Mladenic, Dunja Grobelnik, Marko Jozef Stefan Inst Dept Knowledge Technol Jamova 39 Ljubljana 1000 Slovenia Carnegie Mellon Univ Sch Comp Sci Machine Learning Dept Pittsburgh PA 15213 USA

ISBN: (纸本)9781424418367

Given publication titles and authors, what can we say about the evolution of scientific topics and communities over time? Which communities shrunk, which emerged, and which split, over time? And, when in time were the turning points? We propose TimeFall, which can automatically answer these questions given a social network/graph that evolves over time. The main novelty of the proposed approach is that it needs no user-defined parameters, relying instead on the principle of Mnimum Description Length (MDL), to extract the communities, and to find good cut-points in time when communities change abruptly: a cut-point is good, if it leads to shorter data description. We illustrate our algorithm on synthetic and large real datasets, and we show that the results of the TimeFall agree with human intuition.

关键词： data description

来源：评论

学校读者我要写书评

暂无评论

Optimal Feature Subset Selection for pattern Classification and recognition Using Spectral Entropy as a Complexity Measure from Alcohol and Sleep EEG data 1

Optimal Feature Subset Selection for Pattern Classification ...

引用

1st IEEE international Conference on Innovations in High Speed Communication and Signal Processing, IHCSP 2023

作者： Singh, Takveer Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350345957

The quantity of unprocessed data in multi-channel EEG analysis is enormous. Most datasets have some level of noise or redundancy, which could lower the accuracy of any relevant features that are uncovered. This result in a rise in computational complexity and a corresponding rise in the importance of concerns related to memory consumption. Consequently, feature selection has become the matter of significant research in the arenas of machine learning and statistics since it is crucial for efficient analysis of data while needing less memory and time. Based on the findings of this study, selecting features with high class separability from multichannel EEG recordings is an efficient method for performing supervised learning tasks. With this study, we intend to test the following theory: The best feature subset will have features that are substantially linked with the class labels but not connected with each other. Using the same alcoholic EEG database as these other investigations, we created and compared three feature selection algorithms. The purpose here is to use class knowledge in a feature selection technique to enhance the accuracy with which classes may be detected. © 2023 IEEE.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

Feature Selection for Multi-Label learning 24

Feature Selection for Multi-Label Learning

引用

1st international workshop on Social Influence Analysis / 24th international Joint Conference on Artificial Intelligence (IJCAI)

作者： Spolaor, Newton Monard, Maria Carolina Lee, Huei Diana Univ Sao Paulo Inst Math & Comp Sci Lab Computat Intelligence Sao Carlos Brazil State Univ West Parana Lab Bioinformat Foz Do Iguacu Brazil

ISBN: (纸本)9781577357384

Feature Selection plays an important role in machine learning and data mining, and it is often applied as a data pre-processing step. This task can speed up learning algorithms and sometimes improve their performance. In multi-label learning, label dependence is considered another aspect that can contribute to improve learning performance. A replicable and wide systematic review performed by us corroborates this idea. Based on this information, it is believed that considering label dependence during feature selection can lead to better learning performance. The hypothesis of this work is that multi-label feature selection algorithms that consider label dependence will perform better than the ones that disregard it. To this end, we propose multi-label feature selection algorithms that take into account label relations. These algorithms were experimentally compared to the standard approach for feature selection, showing good performance in terms of feature reduction and predictability of the classifiers built using the selected features.

关键词： Feature Selection

来源：评论

学校读者我要写书评

暂无评论

Computational molecular biology of genome expression and regulation

引用

1st international Conference on pattern recognition and machine Intelligence, PReMI 2005

作者： Zhang, Michael Q. Cold Spring Harbor Laboratory 1 Bungtown Road Cold Spring Harbor NY 11724 United States

ISBN: (纸本)3540305068

Technological advances in experimental and computational molecular biology have revolutionized the whole fields of biology and medicine. Large-scale sequencing, expression and localization data have provided us with a great opportunity to study biology at the system level. I will introduce some outstanding problems in genome expression and regulation network in which better modern statistical and machine learning technologies are desperately needed. Recent revolution in genomics has transformed life science. For the first time in history, mankind has been able to sequence the entire human own genome. Bioinformatics, especially computational molecular biology, has played a vital role in extracting knowledge from vast amount of information generated by the high throughput genomics technologies. Today, I am very happy to deliver this key lecture at the First international Conference on pattern recognition and machine Intelligence at the world renowned Indian statistical Institute (ISI) where such luminaries as Mahalanobis, Bose, Rao and others had worked before. And it is very timely that genomics has attracted new generation of talented young statisticians, reminding us the fact that statistics was essentially conceived from and continuously nurtured by biological problems. pattern/rule recognition is at the heart of all learning process and hence of all disciplines of sciences, and comparison is the fundamental method: it is the similarities that allow inferring common rules;and it is the differences that allow deriving new rules. Gene expression, normally referring to the cellular processes that lead to protein production, is controlled and regulated at multiple levels. Cells use this elaborate system of "circuits" and "switches" to decide when, where and by how much each gene should be turned on (activated, expressed) or off (repressed, silenced) in response to environmental clues. Genome expression and regulation refer to coordinated expression and regulation of m

关键词： Genetic engineering

来源：评论

学校读者我要写书评

暂无评论

1st international Conference on Computational Intelligence in pattern recognition, CIPR 2019

1st International Conference on Computational Intelligence i...

引用

1st international Conference on Computational Intelligence in pattern recognition, CIPR 2019

ISBN: (纸本)9789811390418

The proceedings contain 88 papers. The special focus in this conference is on Computational Intelligence in pattern recognition. The topics include: Classification of Speech and Song Using Co-occurrence-Based Approach;Intelligent Analysis for Personality Detection on Various Indicators by Clinical Reliable Psychological TTH and stress Surveys;automatic Multilingual System from Speech;an Improved data Hiding Scheme Through Image Interpolation;generalization of Multi-bit Encoding Function Based data Hiding Scheme;a machine learning Approach to Comment Toxicity Classification;a Minutia Detection Approach from Direct Gray-Scale Fingerprint Image Using Hit-or-Miss Transformation;face Identification via strategic Combination of Local Features;a study on Reversible Image Watermarking Using Xilinx System Generator;a Novel Enhancement and Segmentation of Color Retinal Image Based on Fuzzy Measure and Fuzzy Integral;SVM and MLP Based Segmentation and recognition of Text from Scene Images Through an Effective Binarization Scheme;user Identification and Authentication Through Voice Samples;template Matching for Kinship Verification in the Wild;Attack Prevention Scheme for Privacy Preservation (APSP) Using K Anonymity in Location Based Services for IoT;statistical Analysis of the UNSW-NB15 dataset for Intrusion Detection;Singer Identification Using MFCC and CRP Features with Support Vector machines;object Proposals Based on Variance Measure;deep learning Approach in Predicting Personal Traits Based on the Way User Type on Touchscreen;Robust Non-blind Video Watermarking Using DWT and QR Decomposition;detection and Classification of Earthquake Images from Online Social Media;On the Cryptanalysis of S-DES Using Binary Cuckoo Search Algorithm;numerical Integration Based Contrast Enhancement Using Simpson’s Method;self Driving Car.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Auxiliary Information Regularized machine for Multiple Modality Feature learning 24

Auxiliary Information Regularized Machine for Multiple Modal...

引用

1st international workshop on Social Influence Analysis / 24th international Joint Conference on Artificial Intelligence (IJCAI)

作者： Yang, Yang Ye, Han-Jia Zhan, De-Chuan Jiang, Yuan Nanjing Univ Natl Key Lab Novel Software Technol Collaborat Innovat Ctr Novel Software Technol & I Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781577357384

In real world applications, data are often with multiple modalities. Previous works assumed that each modality contains sufficient information for target and can be treated with equal importance. However, it is often that different modalities are of various importance in real tasks, e.g., the facial feature is weak modality and the fingerprint feature is strong modality in ID recognition. In this paper, we point out that different modalities should be treated with different strategies and propose the Auxiliary information Regularized machine (ARM), which works by extracting the most discriminative feature subspace of weak modality while regularizing the strong modal predictor. Experiments on binary and multi-class datasets demonstrate the advantages of our proposed approach ARM.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Applications of Discrete Geometry and Mathematical Morphology - First international workshop, WADGMM 2010, Revised Selected Papers

Applications of Discrete Geometry and Mathematical Morpholog...

引用

1st international workshop on Applications of Discrete Geometry and Mathematical Morphology, WADGMM 2010

ISBN: (纸本)9783642323126

The proceedings contain 11 papers. The topics discussed include: connect the dots: the reconstruction of region boundaries from contour sampling points;digital shape analysis with maximal segments;discrete curvature estimation methods for triangulated surfaces;on morphological hierarchical representations for image processing and spatial data clustering;volumetric analysis of digital objects using distance transformation: performance issues and extensions;geometric analysis of 3D electron microscopy data;machine learning as a preprocessing phase in discrete tomography;fast planarity estimation and region growing on GPU;writing reusable digital topology algorithms in a generic image processing framework;and a new image-mining technique for automation of Parkinson's disease research.

关键词：

来源：评论

学校读者我要写书评

暂无评论

1st international Conference on Applied Intelligence and Informatics, AII 2021

1st International Conference on Applied Intelligence and Inf...

引用

1st international Conference on Applied Intelligence and Informatics, AII 2021

ISBN: (纸本)9783030822682

The proceedings contain 30 papers. The special focus in this conference is on Applied Intelligence and Informatics. The topics include: Key Techniques and Challenges for Processing of Heart Sound Signals;enhanced Signal Processing Using Modified Cyclic Shift Tree Denoising;a machine learning Driven Android Based Mobile Application for Flower Identification;a Generative Text Summarization Model Based on Document structure Neural Network;human Gender Detection from Facial Images Using Convolution Neural Network;few-Shot learning for Tamil Handwritten Character recognition Using Deep Siamese Convolutional Neural Network;A CNN Based Model for Venomous and Non-venomous Snake Classification;recognition of Dysfluency in Speech: A Bidirectional Long-Short Term Memory Based Approach;distributed Denial of Service Attack Detection Using machine learning and Class Oversampling;glaucoma Detection Using Inception Convolutional Neural Network V3;scientific Metrological Analysis of Government Services Based on Big data Analysis and Visualization Software Driven by Information Technology;violent Video Event Detection: A Local Optimal Oriented pattern Based Approach;human Age Estimation Using Deep learning from Gait data;an Error Resilient Video Transmission in Ad Hoc Network Using Error Diffusion Block Truncation Coding;ALO: AI for Least Observed People;COVID-Hero: machine learning Based COVID-19 Awareness Enhancement Mobile Game for Children;Literature Classification Model of Deep learning Based on BERT-BiLstM——Taking COVID-19 as an Example;identifying Relevant stakeholders in Digital Healthcare;COVID-19 Detection Using Chest X-Ray Images with a RegNet structured Deep learning Model;mixed Bangla-English Spoken Digit Classification Using Convolutional Neural Network;iConDet: An Intelligent Portable Healthcare App for the Detection of Conjunctivitis.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Designing intelligent systems for online education: Open challenges and future directions 1

Designing intelligent systems for online education: Open cha...

引用

1st international workshop on Enabling data-Driven Decisions from learning on the Web, L2D 2021

作者： Dessì, Danilo Käser, Tanja Marras, Mirko Popescu, Elvira Sack, Harald Epfl Switzerland Fiz Karlsruhe - Leibniz Institute for Information Infrastructure Germany Karlsruhe Institute of Technology Institute Aifb Germany University of Craiova Romania

The design and delivering of platforms for online education is fostering increasingly intense research. Scaling up education online brings new emerging needs related with hardly manageable classes, overwhelming content alternatives, and academic dishonesty while interacting remotely, as examples. However, with the impressive progress of the data mining and machine learning fields, combined with the large amounts of learning-related data and high-performance computing, it has been possible to gain a deeper understanding of the nature of learning and teaching online. Methods at the analytical and algorithmic levels are constantly being developed and hybrid approaches are receiving an increasing attention. Recent methods are analyzing not only the online traces left by students a posteriori, but also the extent to which this data can be turned into actionable insights and models, to support the above needs in a computationally efficient, adaptive and timely way. In this paper, we present relevant open challenges lying at the intersection between the machine learning and educational communities, that need to be addressed to further develop the field of intelligent systems for online education. Several areas of research in this field are identified, such as data availability and sharing, time-wise and multi-modal data modelling, generalizability, fairness, explainability, interpretability, privacy, and ethics behind models delivered for supporting education. Practical challenges and recommendations for possible research directions are provided for each of them, paving the way for future advances in this field. © 2021 CEUR-WS. All rights reserved.

关键词： E-learning

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59页 << < 36 37 38 39 40 41 42 43 44 45 > >>

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：