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

325 篇 会议
155 篇 期刊文献
2 篇 学位论文

馆藏范围

482 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

417 篇 工学
- 195 篇 计算机科学与技术...
- 118 篇 电气工程
- 68 篇 控制科学与工程
- 55 篇 软件工程
- 46 篇 信息与通信工程
- 35 篇 仪器科学与技术
- 30 篇 机械工程
- 25 篇 生物医学工程（可授...
- 24 篇 测绘科学与技术
- 16 篇 电子科学与技术（可...
- 16 篇 环境科学与工程（可...
- 13 篇 石油与天然气工程
- 10 篇 生物工程
- 6 篇 材料科学与工程（可...
- 6 篇 动力工程及工程热...
- 6 篇 化学工程与技术
- 6 篇 航空宇航科学与技...
- 5 篇 光学工程
101 篇 理学
- 29 篇 数学
- 19 篇 系统科学
- 17 篇 物理学
- 15 篇 生物学
- 10 篇 地球物理学
- 9 篇 化学
- 5 篇 统计学（可授理学、...
54 篇 医学
- 36 篇 临床医学
- 9 篇 基础医学(可授医学...
42 篇 管理学
- 36 篇 管理科学与工程(可...
26 篇 农学
- 15 篇 农业资源与环境
- 9 篇 作物学
6 篇 教育学
3 篇 文学
2 篇 法学
1 篇 哲学
1 篇 经济学
1 篇 军事学

主题

482 篇 sorting algorith...
88 篇 classification a...
50 篇 feature extracti...
40 篇 support vector n...
36 篇 classifiers
31 篇 algorithms
30 篇 taxonomy
25 篇 training
24 篇 dataset
23 篇 support vector m...
22 篇 functional train...
20 篇 image classifica...
19 篇 pattern recognit...
16 篇 sorting programs
15 篇 algorithm design...
15 篇 classification
15 篇 accuracy
14 篇 pattern classifi...
13 篇 sorting
13 篇 learning (artifi...

机构

3 篇 cairo univ fac c...
3 篇 sun yat sen univ...
2 篇 univ firenze dip...
2 篇 princeton univ p...
2 篇 univ fed rio gra...
2 篇 univ calif davis...
2 篇 natl tsing hua u...
2 篇 univ cent florid...
2 篇 mit cambridge ma...
2 篇 univ uppsala dep...
2 篇 shanghai jiao to...
2 篇 socomec vicenza
2 篇 université de bo...
2 篇 hong kong inst e...
2 篇 johns hopkins un...
1 篇 nanjing univ pos...
1 篇 int inst geoinfo...
1 篇 beihang univ fer...
1 篇 univ reading sch...
1 篇 univ hosp leuven...

作者

5 篇 nong ge
4 篇 yannick berthoum...
4 篇 lionel bombrun
3 篇 chan wai hong
3 篇 wu yi
3 篇 aurelien schutz
2 篇 babaeizadeh saee...
2 篇 janson s
2 篇 tresca giulia
2 篇 wang ping
2 篇 de paris jean-mi...
2 篇 chaudhury santan...
2 篇 hassanien aboul ...
2 篇 fill ja
2 篇 hua yifan
2 篇 liu jun
2 篇 ferrari luca
2 篇 desouza guilherm...
2 篇 zheng shengan
2 篇 wang zhe

语言

446 篇 英文
23 篇 其他
11 篇 中文
2 篇 土耳其文

检索条件"主题词=Sorting Algorithm"

共 482 条记录，以下是411-420 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：

X-DOG: An Intelligent X-ray-based Dangerous Goods Detection and Automatic Alarm System

X-DOG: An Intelligent X-ray-based Dangerous Goods Detection ...

引用

IEEE International Conference on Green Computing and Communications

作者： Yu Shi Lai Wei Xiaolong Xu Yige Xu Haoran Gao Be Honors Schoo Nnjing Universiy of Poss nd TeecounicionsTongd Coege Nnjing Universiy of Poss nd TeecounicionsSchoo of Couer Science Nnjing Universiy of Poss nd TeecounicionsBe Honors Schoo Nnjing Universiy of Poss nd TeecounicionsSchoo of Inforion Engineering Wuhn Universiy of Technoogy

ISBN: (数字)9781728176475

ISBN: (纸本)9781728176482

X-ray-based security inspection systems are widely used in public places, such as airports, train stations and other critical locations with a large-scale of crowds. However, security checks manually are not efficient enough. Current X-ray-based automatic detection methods, including deep learning and conventional ways, usually face low accuracy, poor universality, and other weakness. In this paper, we proposed an X-ray-based dangerous goods detection scheme named SSD-X, an improved SSD (Single Shot Multi-Box Detector) object detection algorithm, and built X-DOG: an intelligent X-ray-based dangerous goods detection and automatic alarm system with SSD-X. First, in consideration of the position uncertainty and the overlap of objects, multiple data enhancement is utilized to effectively improve the accuracy and ameliorate the overfitting phenomenon. To solve the problem of unbalanced positive and negative samples in detection algorithms, focal loss is adopted to the confidence loss function so as to accelerate the rate of convergence. What's more, soft-NMS is added to enhance performance of detection of dense objects. We built a portable detecting system X-DOG implemented with SSD-X, which can run on mobile platform. Real time detecting and automatic alarming functions are implemented in X-DOG. Compared with the baseline algorithm, SSD-X shows the better performance in our experiments.

关键词： X-ray imaging Servers Object detection Feature extraction Classification algorithms Detection algorithms Convergence Detection algorithms Object detection sorting algorithm Servers X-ray imaging Feature extraction Hazardous goods Converge

来源：评论

学校读者我要写书评

暂无评论

A Study of Land Cover Classification Using ALOS/PALSAR Polarimetric Data

A Study of Land Cover Classification Using ALOS/PALSAR Polar...

引用

7th European Conference on Synthetic Aperture Radar

作者： Masato Ohki Masanobu Shimada Japan Aerospace Exploration Agency Earth Observation Research Centre Japan

ISBN: (纸本)9783800730841

We applied various polarimetric decomposition and classification algorithms to the ALOS/PALSAR polarimetry data and evaluated its capabilities of land-cover characteristics identification and its application. We used some known algorithms without changes, or modified for our study. The results show several algorithms work well for PALSAR data. For example, the unsupervised Wishart classification is found to be effective method to identify the land-cover characteristics. The features of PALSAR observation; high resolution, global coverage, and strategic data acquisition, enable us to investigate land-cover characteristics and its changes.

关键词： land cover sorting algorithm polarimetry algorithms

来源：评论

学校读者我要写书评

暂无评论

Data Classification combining Self-Organizing Maps and Informative Nearest Neighbor

Data Classification combining Self-Organizing Maps and Infor...

引用

International Joint Conference on Neural Networks

作者： Leandro J. Moreira Leandro A. Silva Graduate Program in Electrical Engineering and Computing Mackenzie Presbyterian University Sao Paulo Brazil Graduate Program in Electrical Engineering & Computing Mackenzie Presbyterian University Sao Paulo Brazil

ISBN: (纸本)9781509006212

The task of classifying data has been addressed in various works, and has been utilized in various areas of application, such as medicine, industry, marketing, financial market and many others. This work will present a data classifier proposal that combines the SOM (Self-Organizing Map) neural network with INN (Informative Nearest Neighbors). The combination of these two algorithms will be called in this work as SOM-INN. The classification will be done in a two steps task: in the first the SOM has a functionality to reduce the dataset through a process that utilizes the winning neuron concept and, in the second step, the dataset objects selected will be utilized as reference for the INN algorithm to decide about the classification utilizing the most informative object of the reduced dataset. Experiments using 14 public datasets will be made comparing classic classification algorithms from the indicators of accuracy and time consumed in the classification process. The results obtained show that the proposed SOM-INN algorithm, when compared with the other classifiers, presents better accuracy rates in databases where the border region does not have the object classes well distributed. However, its main differential is in the classification time, which is extremely important for real applications.

关键词： Classification algorithms Training Neurons Proposals Prototypes Measurement Self-organizing feature maps self-organising feature maps sorting algorithm Nearest neighbor Neurons PROTOTYPE Functional training Dataset Pharmaceutical Industry pubs data classification GRHL3 gene

来源：评论

学校读者我要写书评

暂无评论

Research of Large-Scale and Complex Agricultural Data Classification algorithms Based on the Spatial Variability

Research of Large-Scale and Complex Agricultural Data Classi...

引用

The 9th International Conference on Computer and Computing Technologies in Agriculture (CCTA 2015)

作者： Hang Chen Guifen Chen Lixia Cai Yuqin Yang College of Information Technology Jilin Agricultural University Institute of Scientific and Technical Information of Jilin

ISBN: (纸本)9783319483566

In the actual classification problems, as a result of lack of clear boundary information between classification objects, that could lead to loss of classification accuracy easily. Therefore, this article from the spatial patterns of the sample properties to proceed, fuzzy clustering algorithm is proposed based on the sensitivity of attribute weights, through using the attribute weights to improve the classification capability between confusing samples, that is for researching and analysing soil nutrient spatial data with consecutive years to collect in Nongan town. Then through the analysis of the visualization technology to realize the visualization of the algorithm. Experimental results show that introducing weights portray attribute information could reduce the objective function value, and effectively alleviate the phenomenon of boundary data that cannot distinguish. Ultimately to improve the classification accuracy. Meanwhile, use of MATLAB to form visualization of three-dimensional image. The results provide a basis for to improve the accuracy of data classification and clustering analysis of large and complex agricultural data.

关键词： Large-scale and complex data Spatial variation law Fuzzy clustering Soil nutrients Sensitive attribute weights soil nutrients agricultural statistics Visualization sorting algorithm data classification large sizes MATLAB

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Supervised Classification algorithms for Human Activity Recognition with Inertial Sensors

Evaluation of Supervised Classification Algorithms for Human...

引用

IEEE Sensors Conference

作者： Tahmina Zebin Patricia J. Scully Krikor B. Ozanyan School of EEE University of Manchester UK School of CEAS University of Manchester UK

ISBN: (纸本)9781509010134

The main aim of this work is to compare the performance of different algorithms for human activity recognition by extracting various statistical time domain and frequency domain features from the inertial sensor data. Our results show that Support Vector Machines with quadratic kernel classifier (accuracy: 93.5%) and Ensemble classifier with bagging and boosting (accuracy: 94.6%) outperforms other known activity classification algorithms. A parallel coordinate plot based on visualization of features is used to identify useful features or predictors for separating classes. This enabled exclusion of features that contribute least to classification accuracy in a multi-sensor system (five in our case), made the classifier lightweight in terms of number of useful features, training time and computational load and lends itself to real-time implementation.

关键词： Human Activity Recognition (HAR) Classification Feature Selection Supervised Machine Learning MATLAB sorting algorithm Feature extraction MATLAB inertia sensor Sensor Data Activity recognition Human Activities Classifiers bagging PURSE Support Vector Network Recognition (Psychology)

来源：评论

学校读者我要写书评

暂无评论

Automatic Error Detection from Pointing Device Input Data 13

Automatic Error Detection from Pointing Device Input Data

引用

Annual Meeting of The American Society for Information Science and Technology

作者： Afroza Sultana Karyn Moffatt McGill University

ISBN: (纸本)9780877155454

Although interaction techniques have been extensively studied under controlled laboratory conditions, little is known about their capabilities during unconstrained free tasks. Understanding real world use is particularly important for older adults, as some may find computer input more challenging due to age-related declines in motor skill. As a step towards addressing this gap, we studied the feasibility of using machine-learning techniques. In this study, we emphasized on identifying errors from submovement behavior, using pen-based data from younger and older adults. We tested four machine-learning algorithms: Decision Trees, Neural Networks, Naive Bayesian Networks, and Rule Induction. Each yielded an accuracy rate around 90%. Moreover, the experiments have identified some useful metrics to classify errors among older adult users.

关键词： Error modeling Classification algorithms Performance measurement Pen based pointing devices Sub-movement analysis sorting algorithm Performance metrics error modeling accuracy rate pointing devices aged person Rule induction Error detection Motor Skills Bayesian networks

来源：评论

学校读者我要写书评

暂无评论

Intrinsic prior for Bayesian classification of texture images

Intrinsic prior for Bayesian classification of texture image...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Aurelien Schutz Lionel Bombrun Yannick Berthoumieu Universite de Bordeaux Institut Polytechnique de Bordeaux Laboratoire IMS Groupe Signal et Image

ISBN: (纸本)9781479928941

This paper introduces an intrinsic prior distribution for supervised classification of texture images. First, we introduce the intrinsic prior distribution as the normal law on a Riemannian manifold. Next, based on this definition, we derive the estimation and classification schemes. Finally, we propose an application for the classification of texture images. Experiments on the VisTex texture database are conducted and demonstrate the interest of the proposed intrinsic classification algorithm.

关键词： GRAIN PATTERN Prior distribution sorting algorithm Image classification Bayesian inference

来源：评论

学校读者我要写书评

暂无评论

Classification of Wheelchair Commands using Brain Computer Interface: Comparison between Able-Bodied Persons and Patients with Tetraplegia

Classification of Wheelchair Commands using Brain Computer I...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Rifai Chai Sai Ho Ling Gregory P. Hunter Yvonne Tran Hung T. Nguyen Key Centre for Health Technologies Faculty of Engineering and Information Technology University

ISBN: (纸本)9781457702150

This paper presents a three-class mental task classification for an electroencephalography based brain computer interface. Experiments were conducted with patients with tetraplegia and able bodied controls. In addition, comparisons with different time-windows of data were examined to find the time window with the highest classification accuracy. The three mental tasks used were letter composing, arithmetic and imagery of a Rubik's cube rolling forward;these tasks were associated with three wheelchair commands: left, right and forward, respectively. An eyes closed task was also recorded for the algorithms testing and used as an additional on/off command. The features extraction method was based on the spectrum from a Hilbert-Huang transform and the classification algorithm was based on an artificial neural network with a fuzzy particle swarm optimization with cross-mutated operation. The results show a strong eyes closed detection for both groups with average accuracy at above 90%. The overall result for the combined groups shows an improved average accuracy of 70.6% at 1s, 74.8% at 2s, 77.8% at 3s, 79.6% at 4s and 81.4% at 5s. The accuracy for individual groups were lower for patients with tetraplegia compared to the able-bodied group, however, does improve with increased duration of the time-window.

关键词： Quadriplegia Particle swarm optimization Paralysis Brain-Computer Interfaces commands Time windows sorting algorithm Wheelchair Patients Religious Missions

来源：评论

学校读者我要写书评

暂无评论

Fault Location Using Wavelet Transform and Independent Component Analysis

Fault Location Using Wavelet Transform and Independent Compo...

引用

CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)

作者： Guilherme T. Alencar Ricardo C. Santos Aline O. Neves Universidade Federal do ABC Santo André São Paulo Brazil

ISBN: (纸本)9781728131863

This paper discusses Wavelet Transform and Independent Component Analysis methods for fault location in transmission lines. Traveling wave principle is used for measuring signals at the transmission line terminals. It is also shown a fault detection and classification algorithm for the pre-location step. The results are promising in all presented steps. In the fault location step the results considering two different methods are compared and the observed errors are within 2%.

关键词： fault diagnosis fault location independent component analysis power transmission faults power transmission lines wavelet transforms Fault location wavelet transforms Independent component analysis Power transmission lines Fault diagnosis Defect detection Transmission Lines sorting algorithm

来源：评论

学校读者我要写书评

暂无评论

LINEAR DISCRIMINANT MULTIPLE KERNEL LEARNING FOR MULTISPECTRAL IMAGE CLASSIFICATION

LINEAR DISCRIMINANT MULTIPLE KERNEL LEARNING FOR MULTISPECTR...

引用

IEEE International Conference on Image Processing

作者： Yanfeng Gu Qingwang Wang Pigang Liu Deshan Zuo Sch. of Electron. & Inf. Eng. Harbin Inst. of Technol. Harbin China

ISBN: (纸本)9781479957521

In the past decade, with the development of kernel-based machine learning, many different multiple kernel learning (MKL) methods were proposed which focus on selecting the pivotal kernel to be preserved and confirming the optimal kernel combination. In this paper, we address the question mentioned above by using subspace projection method and put forward a linear discriminant based MKL (LDMKL) algorithm. LDMKL algorithm reduces the computational burden and keeps the excellent property of MKL in terms of good classification accuracy by finding the optimal projective direction which makes the intraclass scatter minimum and interclass scatter maximum instead of the time-consuming search for optimal kernel combination. Experimental results indicate that LDMKL algorithm provides the best performances among several the state-of-the-art algorithms while demonstrating satisfactory computational efficiency.

关键词： image classification learning (artificial intelligence) LDMKL algorithm interclass scatter maximum intraclass scatter minimum kernel-based machine learning linear discriminant multiple kernel learning method multispectral image classification subspace projection method Accuracy Classification algorithms Image classification Kernel Remote sensing Support vector machines Training Classification linear discriminant analysis (LDA) multiple kernel learning (MKL) spectral images support vector machine (SVM) Image classification Support Vector Network sorting algorithm Kernel Seeds remote sensing Functional training Linear discriminant analysis multi-spectral image Discriminant

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49页 << < 38 39 40 41 42 43 44 45 46 47 > >>

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：