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

192 篇 会议
86 篇 期刊文献
9 册 图书

馆藏范围

287 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

172 篇 工学
- 128 篇 计算机科学与技术...
- 112 篇 软件工程
- 45 篇 信息与通信工程
- 41 篇 光学工程
- 30 篇 生物工程
- 28 篇 生物医学工程（可授...
- 27 篇 机械工程
- 19 篇 控制科学与工程
- 13 篇 仪器科学与技术
- 13 篇 电气工程
- 7 篇 电子科学与技术（可...
- 5 篇 力学（可授工学、理...
- 4 篇 化学工程与技术
- 4 篇 安全科学与工程
- 3 篇 建筑学
111 篇 理学
- 56 篇 数学
- 47 篇 物理学
- 32 篇 生物学
- 19 篇 统计学（可授理学、...
- 6 篇 化学
- 4 篇 系统科学
47 篇 管理学
- 34 篇 图书情报与档案管...
- 18 篇 管理科学与工程(可...
- 9 篇 工商管理
14 篇 医学
- 14 篇 临床医学
- 13 篇 基础医学(可授医学...
- 11 篇 药学(可授医学、理...
6 篇 艺术学
- 6 篇 设计学（可授艺术学...
3 篇 经济学
- 3 篇 应用经济学
3 篇 法学
- 3 篇 社会学
1 篇 教育学

主题

36 篇 pattern recognit...
34 篇 feature extracti...
28 篇 image segmentati...
27 篇 computer vision
25 篇 support vector m...
19 篇 handwriting reco...
19 篇 training
15 篇 image edge detec...
15 篇 accuracy
14 篇 character recogn...
12 篇 optical characte...
12 篇 shape
11 篇 databases
10 篇 kernel
9 篇 face recognition
9 篇 text recognition
8 篇 writing
8 篇 image color anal...
7 篇 computer science
7 篇 image processing

机构

86 篇 computer vision ...
18 篇 department of st...
15 篇 computer vision ...
14 篇 national key lab...
10 篇 department of in...
8 篇 department of co...
8 篇 computer vision ...
8 篇 xiamen key labor...
8 篇 faculty of compu...
7 篇 department of st...
6 篇 shenzhen key lab...
5 篇 graduate school ...
5 篇 computer vision ...
5 篇 faculty of compu...
5 篇 machine vision a...
4 篇 machine vision a...
4 篇 national laborat...
4 篇 department of co...
4 篇 department of co...
4 篇 university of ch...

作者

46 篇 pal umapada
41 篇 umapada pal
16 篇 palaiahnakote sh...
13 篇 p. nagabhushan
11 篇 chanda sukalpa
11 篇 alireza alaei
10 篇 b.b. chaudhuri
10 篇 tong lu
10 篇 shivakumara pala...
9 篇 sukalpa chanda
8 篇 chaudhuri bidyut...
7 篇 ming dong
7 篇 eerola tuomas
7 篇 kälviäinen heikk...
7 篇 liu jianzhuang
7 篇 katrin franke
6 篇 blumenstein mich...
6 篇 liu xin
6 篇 alaei alireza
6 篇 lu tong

语言

278 篇 英文
8 篇 其他
1 篇 中文

检索条件"机构=Department of Computer Vision and Pattern Recognition"

共 287 条记录，以下是121-130 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：

Using Modified Contour Features and SVM Based Classifier for the recognition of Persian/Arabic Handwritten Numerals

Using Modified Contour Features and SVM Based Classifier for...

引用

International Conference on Advances in pattern recognition (ICAPR)

作者： Alireza Alaei Umapada Pal P. Nagabhushan Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

In this paper, we propose a robust and efficient feature set based on modified contour chain code to achieve higher recognition accuracy of Persian/Arabic numerals. In classification part, we employ support vector machine (SVM) as classifier. Feature set consists of 196 dimensions, which are the chain-code direction frequencies in the contour pixels of input image. We evaluated our scheme on 80,000 handwritten samples of Persian numerals. Using 60,000 samples for training, we tested our scheme on other 20,000 samples and obtained 98.71% correct recognition rate. Further, we obtained 99.37% accuracy using five-fold cross validation technique on 80,000 dataset.

关键词： Support vector machines Support vector machine classification Handwriting recognition pattern recognition Feature extraction Shape Frequency Pixel Writing Optical character recognition software

来源：评论

学校读者我要写书评

暂无评论

Identification of embedded mathematical expressions in scanned documents

Identification of embedded mathematical expressions in scann...

引用

International Conference on pattern recognition

作者： U. Garain B.B. Chaudhuri A.R. Chaudhuri Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India Department of Computer Science & Engineering Jadavpur University Kolkata India

Efficient extraction of mathematical expressions is considered as an important pre-processing step to apply existing OCR systems to convert scientific papers into their electronic format. In this correspondence, a technique for extracting embedded (or in-line) expressions has been presented. The proposed method for expression extraction initially invokes an existing OCR to recognize the input document. Several features including word n-grams (a statistical analysis of a corpus of scientific documents reveals that the word level n-gram profile for sentences containing embedded expressions is quite different from that of the sentences without any expression) are computed on sentence level to spot sentences containing expressions. Expression zones are pin pointed by exploiting OCR inability to handle expressions and by using some common typographical aspects followed in typing mathematical expressions. Experimental results on a considerable size of dataset show high efficiency of the proposed technique.

关键词： Optical character recognition software Text recognition Character recognition pattern recognition computer vision computer science Statistical analysis Embedded computing Engines Matrix converters

来源：评论

学校读者我要写书评

暂无评论

Entropy Computations of Document Images in Run-Length Compressed Domain

Entropy Computations of Document Images in Run-Length Compre...

引用

International Conference on Signal and Image Processing (ICSIP)

作者： P. Nagabhushan Mohammed Javed B.B. Chaudhuri Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Compression of documents, images, audios and videos have been traditionally practiced to increase the efficiency of data storage and transfer. However, in order to process or carry out any analytical computations, decompression has become an unavoidable pre-requisite. In this research work, we have attempted to compute the entropy, which is an important document analytic directly from the compressed documents. We use Conventional Entropy Quantifier (CEQ) and Spatial Entropy Quantifiers (SEQ) for entropy computations [1]. The entropies obtained are useful in applications like establishing equivalence, word spotting and document retrieval. Experiments have been performed with all the data sets of [1], at character, word and line levels taking compressed documents in run-length compressed domain. The algorithms developed are computational and space efficient, and results obtained match 100% with the results reported in [1].

关键词： Entropy Image coding Feature extraction Energy measurement Data mining Position measurement

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of Persian/Arabic Handwritten Character recognition

A Comparative Study of Persian/Arabic Handwritten Character ...

引用

International Workshop on Frontiers in Handwriting recognition

In recent years, many techniques for the recognition of Persian/Arabic handwritten documents have been proposed by researchers. To test the promises of different features extraction and classification methods and to provide a new benchmark for future research, in this paper a comparative study of Persian/Arabic handwritten character recognition using different feature sets and classifiers is presented. Feature sets used in this study are computed based on gradient, directional chain code, shadow, under-sampled bitmap, intersection/junction/endpoint, and line-fitting information. Support Vector Machines (SVMs), Nearest Neighbour (NN), k-Nearest Neighbour (k-NN) are used as different classifiers. We evaluated the proposed systems on a standard dataset of Persian handwritten characters. Using 36682 samples for training, we tested the proposed recognition systems on other 15338 samples and their detailed results are reported. The best correct recognition of 96.91% is obtained in this comparative study.

关键词： Feature extraction Character recognition Handwriting recognition Shape Support vector machines Accuracy Training

来源：评论

学校读者我要写书评

暂无评论

Multi-feature canonical correlation analysis for face photo-sketch image retrieval 13

Multi-feature canonical correlation analysis for face photo-...

引用

21st ACM International Conference on Multimedia, MM 2013

作者： Gong, Dihong Li, Zhifeng Liu, Jianzhuang Qiao, Yu Shenzhen Key Lab of Computer Vision and Pattern Recognition Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology China Media Lab Huawei Technologies Co. Ltd. China Department of Information Engineering Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781450324045

Automatic face photo-sketch image retrieval has attracted great attention in recent years due to its important applications in real life. The major difficulty in automatic face photo-sketch image retrieval lies in the fact that there exists great discrepancy between the different image modalities (photo and sketch). In order to reduce such discrepancy and improve the performance of automatic face photo-sketch image retrieval, we propose a new framework called multi-feature canonical correlation analysis (MCCA) to effectively address this problem. The MCCA is an extension and improvement of the canonical correlation analysis (CCA) algorithm using multiple features combined with two different random sampling methods in feature space and sample space. In this framework, we first represent each photo or sketch using a patch-based local feature representation scheme, in which histograms of oriented gradients (HOG) and multi-scale local binary pattern (MLBP) serve as the local descriptors. Canonical correlation analysis (CCA) is then performed on a collection of random subspaces to construct an ensemble of classifiers for photo-sketch image retrieval. Extensive experiments on two public-domain face photo-sketch datasets (CUFS and CUFSF) clearly show that the proposed approach obtains a substantial improvement over the state-of-the-art. Copyright © 2013 ACM.

关键词： Image retrieval

来源：评论

学校读者我要写书评

暂无评论

A New Dataset of Persian Handwritten Documents and Its Segmentation

A New Dataset of Persian Handwritten Documents and Its Segme...

引用

Iranian Machine vision and Image Processing (MVIP)

作者： Alireza Alaei P. Nagabhushan Umapada Pal Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

In document image analysis and especially in handwritten document image recognition, standard datasets play vital roles for evaluating performances of algorithms and comparing results obtained by different groups of researchers. In this paper, an unconstrained Persian handwritten text dataset (PHTD) is introduced. The PHTD contains 140 handwritten documents of three different categories written by 40 individuals. Total number of text-lines and words/subwords in the dataset are 1787 and 27073, respectively. In most of the PHTD documents either an overlapping or a touching text-lines is present. The average number of text-lines in documents of the PHTD is 13. Two types of ground truths based on pixels information and content information are generated for the dataset. Providing these two types of ground truths for the PHTD, it can be utilized in many areas of document image processing such as sentence recognition/understanding, text-line segmentation, word segmentation, word recognition, and character segmentation. To provide a framework for other researches, recent text-line segmentation results on this dataset are also reported.

关键词： Image segmentation Handwriting recognition Databases Character recognition Image recognition Text recognition

来源：评论

学校读者我要写书评

暂无评论

Extraction of line-word-character segments directly from run-length compressed printed text-documents

Extraction of line-word-character segments directly from run...

引用

National Conference on computer vision, pattern recognition, Image Processing and Graphics (NCVPRIPG)

作者： Mohammed Javed P. Nagabhushan B.B. Chaudhuri Department of Studies in Computer Science University of Mysore Mysore India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Segmentation of a text-document into lines, words and characters, which is considered to be the crucial preprocessing stage in Optical Character recognition (OCR) is traditionally carried out on uncompressed documents, although most of the documents in real life are available in compressed form, for the reasons such as transmission and storage efficiency. However, this implies that the compressed image should be decompressed, which indents additional computing resources. This limitation has motivated us to take up research in document image analysis using compressed documents. In this paper, we think in a new way to carry out segmentation at line, word and character level in run-length compressed printed-text-documents. We extract the horizontal projection profile curve from the compressed file and using the local minima points perform line segmentation. However, tracing vertical information which leads to tracking words-characters in a run-length compressed file is not very straight forward. Therefore, we propose a novel technique for carrying out simultaneous word and character segmentation by popping out column runs from each row in an intelligent sequence. The proposed algorithms have been validated with 1101 text-lines, 1409 words and 7582 characters from a data-set of 35 noise and skew free compressed documents of Bengali, Kannada and English Scripts.

关键词： Image coding Image segmentation Optical character recognition software Text analysis Image analysis Facsimile

来源：评论

学校读者我要写书评

暂无评论

A New Text-Line Alignment Approach Based on Piece-Wise Painting Algorithm for Handwritten Documents

A New Text-Line Alignment Approach Based on Piece-Wise Paint...

引用

International Conference on Document Analysis and recognition

Because of writing styles of different individuals, some of the text-lines may be curved in shape. For recognition of such text-lines, their proper alignment is necessary. In this paper, we propose a text-line alignment technique based on painting algorithm. Here at first, Piece-wise Painting Algorithm (PPA) is used to get a number of black and white rectangular patches all along the text-line for text-line alignment. Identifying the degree of oscillation of the input text-line, some candidate pixels are also obtained based on horizontal projection and center points of the black patches. Using the degree of oscillation of the input text image and the candidate pixels a curve or straight line is fit to trace the baseline. Subsequently, all components of the text-line are deskewed based on analyzing the characteristic of the fit curve or line to align the components with respect to the horizontal imaginary baseline. The proposed algorithm was evaluated with 128 Persian handwritten text-lines containing 4317 sub words. Experimental analysis showed that 92.31% of the sub words were accurately aligned. Further, the proposed algorithm was tested with another Persian handwritten text-lines dataset [6] and remarkable results were achieved.

关键词： Oscillators Painting Polynomials Algorithm design and analysis Curve fitting Estimation pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Fine Classification of Unconstrained Handwritten Persian/Arabic Numerals by Removing Confusion amongst Similar Classes

Fine Classification of Unconstrained Handwritten Persian/Ara...

引用

International Conference on Document Analysis and recognition

ISBN: (纸本)9781424445004

In this paper, we propose two types of feature sets based on modified chain-code direction frequencies in the contour pixels of input image and modified transition features (horizontally and vertically). A multi-level support vector machine (SVM) is proposed as classifier to recognize Persian isolated digits. In first level, we combine similar shaped numerals into a single group and as result; we obtain 7 classes instead of 10 classes. We compute 196-dimension chain-code direction frequencies as features to discriminate 7 classes. In the second level, classes containing more than one numeral because of high resemblance in their shapes are considered. We use modified transition features (horizontally and vertically) for discriminating between two overlapping classes (0 and 1). To separate another overlapping group containing three numerals 2, 3 and 4 we first eliminate common parts of these digits (tail) and then compute chain code features. We employ SVM classifier for the classification and evaluate our scheme on 80,000 handwritten samples of Persian numerals [10]. Using 60,000 samples for training, we tested our scheme on other 20,000 samples and obtained 99.02% accuracy.

关键词： Support vector machines Support vector machine classification Shape Character recognition Handwriting recognition Frequency Natural languages pattern recognition Testing Text analysis

来源：评论

学校读者我要写书评

暂无评论

Collaborative representation based fine-grained species recognition

Collaborative representation based fine-grained species reco...

引用

International Conference on Image and vision Computing New Zealand, IVCNZ

作者： Tapabrata Chakraborti Brendan McCane Steven Mills Umapada Pal Department of Computer Science University of Otago Dunedin New Zealand Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781509027491

Fine-grained Visual Categorization (FGVC) is an open problem in computer vision due to subtle differences between categories. The present paper demonstrates that Collaborative Representation based Classification (CRC) can address this problem successfully. Instead of the traditional discriminative approach of classification, CRC takes a co-operative approach by representing the query image as a weighted collaboration of training images across all classes in the feature space. The superior performance of CRC compared to some other modern classifiers including SVM is shown in this work using several popular descriptors like GIST+Color, SIFT and CNN features with Species recognition chosen as the representative FGVC problem. Besides experiments on the Oxford 102 Flowers and CUB200-2011 Bird benchmarks, the present work also introduces a new challenging dataset NZ Birds v1.0 with 600 images of 30 New Zealand endemic and native bird species.

关键词： Birds Collaboration Training Visualization Image recognition Face recognition Cost function

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29页 << < 9 10 11 12 13 14 15 16 17 18 > >>

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：