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1381-1390 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：

Combining One-Class Classifiers for Imbalanced Classification of Breast thermogram Features

Combining One-Class Classifiers for Imbalanced Classificatio...

引用

4th international Workshop on Computational Intelligence in Medical Imaging (CIMI)

作者： Krawczyk, Barlosz Schaefer, Gerald Wozniak, Michai Wroclaw Univ Technol Dept Syst & Comp Networks PL-50370 Wroclaw Poland Univ Loughborough Dept Comp Sci Loughborough Leics England

ISBN: (纸本)9781467359191

thermography provides an interesting modality for diagnosing breast cancer as it is a non-contact, non-invasive and passive technique that is able to detect small tumors, which in turn can lead to earlier diagnosis. We perform computer-aided diagnosis of breast thermograms based on image features describing bilateral differences in regions of interest and a pattern classification approach that learns from previous examples. As is often the case in medical diagnosis, such training sets are imbalanced as typically (many) more benign cases get recorded compared to malignant cases. In this paper, we address this problem and perform classification using an ensemble of one-class classifiers. One-class classification uses samples from a single distribution to derive a decision boundary, and employing this method on the minority class can significantly boost its recognition rate and hence the sensitivity of our approach. We combine several one-class classifiers using a random subspace approach and a diversity measure to select members of the committee. We show that our proposed technique works well and leads to significantly improved performance compared to a single one-class predictor as well as compared to state-of-the-art classifier ensembles for imbalanced data.

关键词： medical imaging breast thermogram breast cancer machine learning one-class classification multiple classifier system imbalanced classification

来源：评论

学校读者我要写书评

暂无评论

Superpixel Clustering and Planar Fit Segmentation of 3D LIDAR Point Clouds

Superpixel Clustering and Planar Fit Segmentation of 3D LIDA...

引用

4th international conference on Computing for Geospatial Research and Application (COM.Geo)

作者： Mahmoudabadi, Hamid Shoaf, Timothy Olsen, Michael J. Oregon State Univ Sch Civil & Construct Engn Corvallis OR 97330 USA Oregon State Univ Dept Elect Engn & Comp Sci Corvallis OR 97330 USA

ISBN: (纸本)9780769550121

Terrestrial laser scanning (TLS, also called ground-based Light Detection and Ranging, LIDAR) is an effective data acquisition method capable of high precision, detailed 3D models for surveying natural environments. However, despite the high density, and quality, of the data itself, the data acquired contains no direct intelligence necessary for further modeling and analysis - merely the 3D geometry (XYZ), 3-component color (RGB), and laser return signal strength (I) for each point. One common task for LIDAR data processing is the selection of an appropriate methodology for the extraction of geometric features from the irregularly distributed point clouds. Such recognition schemes must accomplish both segmentation and classification. Planar (or other geometrically primitive) feature extraction is a common method for point cloud segmentation;however, current algorithms are computationally expensive and often do not utilize color or intensity information. In this paper we present an efficient algorithm, that takes advantage of both colorimetric and geometric data as input and consists of three principal steps to accomplish a more flexible form of feature extraction. First, we employ a Simple Linear Iterative Clustering (SLIC) superpixel algorithm for clustering and dividing the colorimetric data. Second, we use a plane-fitting technique on each significantly smaller cluster to produce a set of normal vectors corresponding to each superpixel. Last, we utilize a Least Squares Multi-class Support Vector machine (LSMSVM) to classify each cluster as either "ground", "wall", or "natural feature". Despite the challenging problems presented by the occlusion of features during data acquisition, our method effectively generates accurate (> 85%) segmentation results by utilizing the color space information, in addition to the standard geometry, during segmentation.

关键词： LIDAR Laser Point Cloud Superpixel machine learning Clustering SVM

来源：评论

学校读者我要写书评

暂无评论

Color image segmentation based-on SVM using mixed features and combined kernel

Color image segmentation based-on SVM using mixed features a...

引用

4th international conference on Intelligence Science and Big data Engineering, IScIDE 2013

作者： Li, Lei Shi, Dong Yan Xu, Jun The Science in NUPT China Pattern Recognition and Intelligent System China Control Theory and Control Engineering China

ISBN: (纸本)9783642420566

Image segmentation occupies the important position in image processing, so both high-efficiency and accurate segmentation are of great importance to image's subsequent research. In this paper, taking the color and texture features into account, the color features are combined with RGB and HSV color space features, and the texture features are made up with the mean value and standard deviation. Considering the advantages of support vector machine (SVM) in classification, we convert the segmentation problem into a classification problem, and we can get the satisfied segmentation result. Genetic Algorithms (GA) is used for the optimization of the parameters in SVM's kernel which is combined with polynomial (poly) and radial basis function (rbf) kernel reasonably by mercer theorem. the experimental results show that we can segment various kinds of color images effectively. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

recognition of sleep dependent memory consolidation with multi-modal sensor data

Recognition of sleep dependent memory consolidation with mul...

引用

international Workshop on Wearable and Implantable Body Sensor Networks (BSN)

作者： Akane Sano Rosalind W. Picard Media Laboratory Massachusetts Institute of Technology Cambridge MA USA

ISBN: (纸本)9781479903313

this paper presents the possibility of recognizing sleep dependent memory consolidation using multi-modal sensor data. We collected visual discrimination task (VDT) performance before and after sleep at laboratory, hospital and home for N=24 participants while recording EEG (electroencepharogram), EDA (electrodermal activity) and ACC (accelerometer) or actigraphy data during sleep. We extracted features and applied machine learning techniques (discriminant analysis, support vector machine and k-nearest neighbor) from the sleep data to classify whether the participants showed improvement in the memory task. Our results showed 60–70% accuracy in a binary classification of task performance using EDA or EDA+ACC features, which provided an improvement over the more traditional use of sleep stages (the percentages of slow wave sleep (SWS) in the 1 st quarter and rapid eye movement (REM) in the 4th quarter of the night) to predict VDT improvement.

关键词： Sleep Accuracy Electroencephalography Hospitals Laboratories Temperature measurement Standards

来源：评论

学校读者我要写书评

暂无评论

Superpixel Clustering and Planar Fit Segmentation of 3D LIDAR Point Clouds

Superpixel Clustering and Planar Fit Segmentation of 3D LIDA...

引用

international conference on Computing for Geospatial Research and Application

作者： Hamid Mahmoudabadi Timothy Shoaf Michael J. Olsen School of Civil and Construction Engineering Oregon State University Department of Electrical Engineering and Computer Science Oregon State University

ISBN: (纸本)9781479903016

Terrestrial laser scanning (TLS, also called ground-based Light Detection and Ranging, LIDAR) is an effective data acquisition method capable of high precision, detailed 3D models for surveying natural environments. However, despite the high density, and quality, of the data itself, the data acquired contains no direct intelligence necessary for further modeling and analysis - merely the 3D geometry (XYZ), 3-component color (RGB), and laser return signal strength (I) for each point. One common task for LIDAR data processing is the selection of an appropriate methodology for the extraction of geometric features from the irregularly distributed point clouds. Such recognition schemes must accomplish both segmentation and classification. Planar (or other geometrically primitive) feature extraction is a common method for point cloud segmentation;however, current algorithms are computationally expensive and often do not utilize color or intensity information. In this paper we present an efficient algorithm, that takes advantage of both colorimetric and geometric data as input and consists of three principal steps to accomplish a more flexible form of feature extraction. First, we employ a Simple Linear Iterative Clustering (SLIC) superpixel algorithm for clustering and dividing the colorimetric data. Second, we use a plane-fitting technique on each significantly smaller cluster to produce a set of normal vectors corresponding to each superpixel. Last, we utilize a Least Squares Multi-class Support Vector machine (LSMSVM) to classify each cluster as either "ground", "wall", or "natural feature". Despite the challenging problems presented by the occlusion of features during data acquisition, our method effectively generates accurate (>85%) segmentation results by utilizing the color space information, in addition to the standard geometry, during segmentation.

关键词： LIDAR Laser Point Cloud Superpixel machine learning Clustering SVM

来源：评论

学校读者我要写书评

暂无评论

AI*IA 2013: Advances in Artificial Intelligence: XIIIth international conference of the Italian Association for Artificial Intelligence, Turin, Italy, December 4-6, 2013. Proceedings 1

引用

丛书名： Lecture Notes in Computer Science

2013年

作者： Mario Alviano, Carmine Dodaro, Francesco Ricca (auth.), Matteo Baldoni, Cristina Baroglio, Guido Boella, Roberto Micalizio (eds.)

ISBN: (数字)9783319035246

ISBN: (纸本)9783319035239;9783319035246

this book constitutes the refereed proceedings of the 13th international conference of the Italian Association for Artificial Intelligence, AI*IA 2013, held in Turin, Italy, in December 2013. the 45 revised full papers were carefully reviewed and selected from 86 submissions. the conference covers broadly the many aspects of theoretical and applied Artificial Intelligence as follows: knowledge representation and reasoning, machine learning, natural language processing, planning, distributed AI: robotics and MAS, recommender systems and semantic Web and AI applications.

关键词：人工智能l。机器人学；数据采矿和知识发现；数理逻辑和正式语言；由抽象设备的计算；用户接口和人的计算机相互作用；模式识别

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of a Mobile Teaching-learning pattern through Atom Publishing Protocol

Design and Implementation of a Mobile Teaching-Learning Patt...

引用

4th international conference on machine Vision (ICMV) - Computer Vision and Image Analysis - pattern recognition and Basic Technologies

作者： Wu Yu Tongji Univ Comp Sci & Technol Dept Shanghai 200092 Peoples R China

ISBN: (纸本)9780819490261

the new technologies set the stage for Mobile learning. In this paper, we explored a Mobile Teaching-learning pattern and its advantages. And then we modeled courses with Atom and Atom Publishing Protocol. Grounded on the pattern and modeling, we implemented mobile learning client side with Apple technologies, which could achieve anytime, anywhere learning. And at last, we discussed the application of our system.

关键词： Atompub Mobile Teaching and learning Apple Technology

来源：评论

学校读者我要写书评

暂无评论

A research of E-learning Based On Ontology

A research of E-learning Based On Ontology

引用

4th international conference on machine Vision (ICMV) - Computer Vision and Image Analysis - pattern recognition and Basic Technologies

作者： Wang, Zhenxing Shanghai Second Polytech Univ Dept Comp Sci Shanghai Peoples R China

ISBN: (纸本)9780819490261

E-learning device is widely used in our daily life. However mobile e-learning machine is not satisfied as expected. Most mobile e-learning device is a static learning device, unable to fulfill the requirement of collaboration, long standby time, usage under strong sunlight. To meet these requirements, we developed a learning machine based on electronic paper. this paper will discuss the software consideration of the device. the software is a knowledge navigation system, the navigation system is based on Ontology. Research shows that combine frame Ontology and description logic together can afford a uniform interface to user application.

关键词： Ontology embedded system EPD

来源：评论

学校读者我要写书评

暂无评论

A Classification Framework of Online learning Activities: based on Grounded theory

A Classification Framework of Online Learning Activities: ba...

引用

4th international conference on machine Vision (ICMV) - Computer Vision and Image Analysis - pattern recognition and Basic Technologies

作者： Zhan, Zehui S China Normal Univ Ctr Educ Informat Technol Guangzhou Guangdong Peoples R China

ISBN: (纸本)9780819490261

the purpose of this paper is to set up a classification framework of online learning activities. Fifty-nine online learning activity cases were collected from seven disciplines. Open coding, axial coding, and selective coding were conducted according to Grounded theory. After step-by-step validation, the classification framework consists of six core categories (Argumentation, Resource Sharing, Collaboration, Inquiry, Evaluation, and Social Network) has been set up. Further study is needed to get more insight into each category and establish effective activity-based instruction models.

关键词： online learning activities classification framework gounded theory

来源：评论

学校读者我要写书评

暂无评论

Application of Complete Local Binary pattern Method for Facial Expression recognition

Application of Complete Local Binary Pattern Method for Faci...

引用

4th international conference on Intelligent Human Computer Interaction (IHCI)

作者： Singh, Suryakant Maurya, Ritesh Mittal, Ajay GLA Univ Dept Comp Sci & Engn Mathura India PEC Univ Tech Dept Comp Sci Chandigarh India

ISBN: (纸本)9781467343695;9781467343671

We propose a novel approach using Complete Local Binary pattern feature generation method for facial expression recognition with the help of Multi-Class Support Vector machine. Complete Local Binary pattern method is an extended version of Local Binary pattern method with a little difference. LBP feature considers only signs of local differences, whereas CLBP feature considers both signs and magnitude of local differences as well as original center gray level value. CLBP and LBP have same computational complexity while CLBP performs better facial expression recognition over LBP using SVM training and multiclass classification with binary SVM classifiers. the experimental result demonstrate the average efficiency of recognition of propose method (35 images) with CLBP is 86.4%, while with LBP and CCV is 84.1255% and 75.83% in the JAFFE database.

关键词： Color Coherence Vector (CCV) Local Binary pattern (LBP) Completed Local Binary pattern (CLBP) Support Vector machine learning and classification

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 << < 135 136 137 138 139 140 141 142 143 144 > >>

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：