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

136 篇 会议
7 篇 期刊文献
1 册 图书

馆藏范围

144 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

102 篇 工学
- 68 篇 计算机科学与技术...
- 39 篇 软件工程
- 15 篇 信息与通信工程
- 14 篇 电气工程
- 12 篇 生物医学工程（可授...
- 11 篇 机械工程
- 11 篇 材料科学与工程（可...
- 11 篇 生物工程
- 10 篇 光学工程
- 10 篇 控制科学与工程
- 8 篇 仪器科学与技术
- 6 篇 力学（可授工学、理...
- 6 篇 化学工程与技术
- 4 篇 电子科学与技术（可...
- 2 篇 建筑学
- 2 篇 环境科学与工程（可...
- 1 篇 动力工程及工程热...
39 篇 理学
- 18 篇 数学
- 15 篇 物理学
- 13 篇 生物学
- 10 篇 统计学（可授理学、...
- 5 篇 化学
- 2 篇 地质学
- 2 篇 系统科学
14 篇 管理学
- 9 篇 图书情报与档案管...
- 6 篇 管理科学与工程(可...
10 篇 医学
- 10 篇 临床医学
- 5 篇 基础医学(可授医学...
- 5 篇 药学(可授医学、理...
1 篇 经济学
- 1 篇 应用经济学
1 篇 农学
1 篇 军事学
1 篇 艺术学

主题

31 篇 pattern recognit...
8 篇 local binary pat...
7 篇 image segmentati...
7 篇 face recognition
6 篇 feature extracti...
6 篇 accuracy
5 篇 machine learning
3 篇 neural networks
3 篇 data mining
3 篇 classification a...
2 篇 fuzzy logic
2 篇 support vector m...
2 篇 deep learning
2 篇 pattern recognit...
2 篇 bibliometrics
2 篇 computational ef...
2 篇 companies
2 篇 cc2530
2 篇 discrete wavelet...
2 篇 expert systems

机构

2 篇 univ antonio nar...
2 篇 state grid tianj...
2 篇 state grid tianj...
2 篇 shandong univers...
2 篇 national laborat...
2 篇 pattern recognit...
2 篇 univ antonio nar...
2 篇 department of co...
1 篇 iiit hyderabad h...
1 篇 jilin univ coll ...
1 篇 school of comput...
1 篇 fraunhofer iosb ...
1 篇 east china jiaot...
1 篇 ecole technol su...
1 篇 pattern recognit...
1 篇 universiti tekno...
1 篇 national center ...
1 篇 shandong inst bu...
1 篇 research group f...
1 篇 infn pisa

作者

3 篇 fred ana
2 篇 yen chih-ta
2 篇 abdullah siti no...
2 篇 c. clausner
2 篇 gutierrez r. m.
2 篇 c. papadopoulos
2 篇 manana g.
2 篇 broun c.c.
2 篇 feinen christian
2 篇 ding ing-jr
2 篇 grzegorzek marci...
2 篇 santosh k.c.
2 篇 s. pletschacher
2 篇 cerquera e. a.
2 篇 wang xin
2 篇 campbell w.m.
2 篇 chandra mouli p....
2 篇 a. antonacopoulo...
1 篇 blumenstein mich...
1 篇 takasu atsuhiro

语言

140 篇 英文
4 篇 其他

检索条件"任意字段=2nd International Conference on Pattern Recognition Applications and Methods, ICPRAM 2013"

共 144 条记录，以下是51-60 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：

A novel color C-V method and its application

引用

2nd international conference on Image Analysis and recognition

作者： Chen, L Zhou, Y Wang, YG Shanghai Jiao Tong Univ Inst Image Proc & Pattern Recognit Shanghai 200030 Peoples R China

ISBN: (纸本)3540290699

C-V method, an active contour model developed by Chan and Vese, has been successfully applied to solve the problem of object detection in grayscale images. In this paper, a novel color C-V method which takes into account of color information and global property is presented. Choosing the appropriate color space for this model is also introduced. Finally, the applications of the proposed method to natural color images and microscopic halftone printing images are given and the experimental results show robust performance especially in case of weak edges and noisy inputs.

关键词： Computational methods

来源：评论

学校读者我要写书评

暂无评论

Face recognition Using LBPH Descriptor and Convolution Neural Network 2

Face Recognition Using LBPH Descriptor and Convolution Neura...

引用

2nd international conference on Intelligent Computing and Control Systems (ICICCS)

作者： Shoba, V. Betcy Thanga Sam, I. Shatheesh Manonmaniam Sundaranar Univ Nesamony Mem Christian Coll Dept Comp Sci Tirunelveli 627012 Tamil Nadu India Manonmaniam Sundaranar Univ Nesamony Mem Christian Coll Dept PG Comp Sci Tirunelveli 627012 Tamil Nadu India

ISBN: (纸本)9781538628423

Face recognition is an exigent problem in Biometrics and Computer Vision. It has become a wonderful field for researchers and can be widely used in applications like surveillance and security also. To create strong and distinct features, increase the inter-personal variations and decrease the intra-personal variations simultaneously remains a demanding problem in facial recognition. In this paper, the researcher explains how to improve the ability of face recognition system using Local Binary pattern (LBP) for feature extraction and Convolution Neural Network (CNN) for classification of the images. The correspondence between the trained images helps CNN to converge faster and achieve better accuracy. There is a great improvement compared to other traditional methods too. To evaluate the accomplishment of this new method, it is found that higher face recognition accuracy can be achieved with less computational cost. The proposed framework is tested on the Yale dataset and achieved an accuracy of 98.6%.

关键词： Convolution Neural Network (CNN) Local Binary pattern Histogram (LBPH)

来源：评论

学校读者我要写书评

暂无评论

Evaluation of Local Binary pattern for Osteoporosis Classification 2

Evaluation of Local Binary Pattern for Osteoporosis Classifi...

引用

2nd IEEE international conference on New Technologies of Information and Communication, NTIC 2022

作者： Meriem, Mebarkia Abdallah, Meraoumia Lotfi, Houam Seddik, Khemaissia Larbi Tebessi University Labget Laboratory Tebessa Algeria

ISBN: (纸本)9781665489744

Deterioration of the bone's microarchitecture and low bone mineral density, which results in increased fragility of bone, are symptoms of the disease osteoporosis, which decreases bone mass. Early osteoporosis identification can prevent the disease and predict fracture risk. Usually, the diagnosis is based on the analysis of X-ray images. However, the healthy and osteoporotic subject radiography shows a great resemblance. This study aims to develop an evaluation of an automatic osteoporosis identification system based on texture analysis. This paper proposes a Local Optimal Oriented pattern (LOOP) to address some of the shortcomings of existing feature descriptors such as Local Binary pattern (LBP) and Local Directional pattern (LDP). Ensemble and SVM learning algorithms were used for the classification task. The obtained results were compared with some state-of-art methods used in the literature. Experimental results show that the proposed approach outperforms the previous binary descriptor in terms of recognition accuracy proving that the proposed approach is efficient for real clinical applications. © 2022 IEEE.

关键词： Local binary pattern

来源：评论

学校读者我要写书评

暂无评论

Grip-pattern Verification for Smart Gun Based on Maximum-Pairwise Comparison and Mean-Template Comparison

Grip-Pattern Verification for Smart Gun Based on Maximum-Pai...

引用

2nd IEEE international conference on Biometrics - Theory, applications and Systems (BTAS 2008)

作者： Shang, Xiaoxin Veldhuis, Raymond N. J. Univ Twente Signals & Syst Grp NL-7500 AE Enschede Netherlands

ISBN: (纸本)9781424427291

In our biometric verification system of a smart gun, the rightful user of a gun is authenticated by grip-pattern recognition. In this work verification will be done using two types of comparison methods, respectively. One is mean-template comparison, where the matching score between a test image and a subject is computed, by comparing the test image to the mean value of training samples of this subject. The other one is maximum-pairwise comparison, where the matching score between a test image and a subject is selected as the maximum, among all the similarity scores resulting from comparison between the test image and each training sample of this subject. Experimental results show that a much lower false-acceptance rate can be obtained at the required false-rejection rate of our system using maximum-pairwise comparison, than mean-template comparison.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

A Star Map recognition Method Based on Multi-layers SOFM Network

A Star Map Recognition Method Based on Multi-layers SOFM Net...

引用

2nd international conference on Information Technology and Management Innovation (ICITMI 2013)

作者： He, Aixiang Wang, Chenchen Zhang, Haining Shandong Inst Business & Technol Jinan Peoples R China

ISBN: (纸本)9783037858646

Putting forward a kind of star identification algorithm based on SOFM neural network. Firstly, using dynamic threshold selection algorithm what is based on supporting vector machine select guide stars to composite the navigation star database, then a recognition system what contain multiple parallel SOFM subnets for star map recognition is designed. Simulated recognition results show that the SOFM network can extract complex feature recognition navigation star from the chart. Compared with the traditional triangle algorithm, this algorithm has better recognition accuracy, robustness and real-time.

关键词： Star pattern recognition SOFM network Triangle algorithm

来源：评论

学校读者我要写书评

暂无评论

Mutual information-based methods to improve local region-of-interest image registration

引用

2nd international conference on Image Analysis and recognition

作者： Wilkie, KP Vrscay, ER Univ Waterloo Dept Appl Math Waterloo ON N2L 3G1 Canada

ISBN: (纸本)3540290699

Current methods of multimodal image registration usually seek to maximize the similarity measure of mutual information (MI) between two images over their region of overlap. In applications such as planned radiation therapy, a diagnostician is more concerned with registration over specific regions of interest (ROI) than registration of the global image space. Registration of the ROI can be unreliable because the typically small regions have limited statistics and thus poor estimates of entropies. We examine methods to improve ROI-based registration by using information from the global image space.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Principal Component Analysis Integrating Mahalanobis Distance for Face recognition

Principal Component Analysis Integrating Mahalanobis Distanc...

引用

2nd international conference on Robot, Vision and Signal Processing (RVSP)

作者： Fan, Zizhu Ni, Ming Sheng, Meibo Wu, Zejiu Xu, Baogen East China Jiaotong Univ Sch Basic Sci Nanchang 330013 Peoples R China East China Jiaotong Univ Sch Econ & Management Nanchang 330013 Peoples R China

ISBN: (纸本)9781479931842

In machine learning and pattern recognition, principal component analysis (PCA) is a very popular feature extraction and dimensionality reduction method for improving recognition performance or computational effiency. It has been widely used in numerous applications, especially in face recognition. Researches often use PCA integrating the nearest neighbor classifier (NNC) based on Euclidean distance (ED) to classify face images. We refer to this method as PCA+ED. However, we have observed that PCA can not significantly improve the recognition performance of NNC based on Euclidean distance through many experiments. The main reason is that PCA can not significantly change the Euclidean distance between samples when many components are used in classification. In order to improve the classification performance in face recognition, we use another distance measure, i.e., Mahalanobis distance (MD), in NNC after performing PCA in this paper. This approach is referred to as PCA+MD. Several experiments show that PCA+MD can significantly improve the classification performance in face recognition.

关键词： pattern recognition principal component analysis (PCA) face recognition Mahalanobis distance (MD) nearest neighbor classifier (NNC)

来源：评论

学校读者我要写书评

暂无评论

Face recognition Using Gray Level Weight Matrix (GLWM)

Face Recognition Using Gray Level Weight Matrix (GLWM)

引用

2nd international conference on Advances in Power Electronics and Instrumentation Engineering (PEIE 2011)

作者： Sabeenian, R. S. Paramasivam, M. E. Dinesh, P. M. Sona SIPRO Salem India

ISBN: (纸本)9783642204982

Face detection is one of the few biometric methods that possess the merits of both high accuracy and low intrusiveness. It also has several applications in areas such as content-based image retrieval, video coding, video conferencing, crowd surveillance, and intelligent human computer interfaces. The purpose of this study is to propose a novel statistical face recognition system with improved performance, based on Gray Level Weight Matrix (GLWM). The process involved in GLWM is an improved version of the Local Binary pattern technique. It has been found out through experiments that the proposed GLWM is more efficient in face recognition.

关键词： Local Binary pattern Gray Level Weight Matrix Face recognition

来源：评论

学校读者我要写书评

暂无评论

Vehicle Detection in Satellite Images by Parallel Deep convolutional Neural Networks

Vehicle Detection in Satellite Images by Parallel Deep convo...

引用

2nd IAPR Asian conference on pattern recognition (ACPR)

作者： Chen, Xueyun Xiang, Shiming Liu, Cheng-Lin Pan, Chun-Hong Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100190 Peoples R China

ISBN: (纸本)9781479921904

Deep convolutional Neural Networks (DNN) is the state-of-the-art machine learning method. It has been used in many recognition tasks including handwritten digits, Chinese words and traffic signs, etc. However, training and test DNN are time-consuming tasks. In practical vehicle detection application, both speed and accuracy are required. So increasing the speeds of DNN while keeping its high accuracy has significant meaning for many recognition and detection applications. We introduce parallel branches into the DNN. The maps of the layers of DNN are divided into several parallel branches, each branch has the same number of maps. There are not direct connections between different branches. Our parallel DNN (PNN) keeps the same structure and dimensions of the DNN, reducing the total number of connections between maps. The more number of branches we divide, the more swift the speed of the PNN is, the conventional DNN becomes a special form of PNN which has only one branch. Experiments on large vehicle database showed that the detection accuracy of PNN dropped slightly with the speed increasing. Even the fastest PNN (10 times faster than DNN), whose branch has only two maps, fully outperformed the traditional methods based on features (such as HOG, LBP). In fact, PNN provides a good solution way for compromising the speed and accuracy requirements in many applications.

关键词： Remote Sensing Object detection Deep convolutional Neural Networks

来源：评论

学校读者我要写书评

暂无评论

Arabic-Jawi Scripts Font recognition Using First-Order Edge Direction Matrix

引用

2nd international Multi-conference on Artificial Intelligence Technology, M-CAIT 2013

作者： Bataineh, Bilal Abdullah, Siti Norul Huda Sheikh Omar, Khairuddin Batayneh, Anas Pattern Recognition Research Group Center For Artificial Intelligence Technology Universiti Kebangsaan Malaysia 43600 Bangi Selangor Malaysia Department of Computer Engineering Yarmouk University 21163 Irbid Jordan

ISBN: (纸本)9783642405662

Document image analysis and recognition (DIAR) techniques are a primary application of pattern recognition. OFR is one of the most important DIAR techniques. The information about font type indicates important information to support human knowledge and other document analysis and recognition techniques. In this paper, a new optical font recognition method for Arabic scripts is proposed based on the First order edge direction matrix, which is an effected simple feature extraction method for binary images. The proposed methods based on several recent methods in pre-processing and feature extraction stages. The performance of the proposed method is compared with the previous OFR methods that based on texture analysis methods in the feature extraction stage. The results show that the proposed method presents the best performance than of other methods in terms of computation time and accuracy. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Feature extraction

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15页 << < 2 3 4 5 6 7 8 9 10 11 > >>

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：