2009 Seventh International Conference on Advances in Pattern Recognition最新文献_第4页

Low-Resolution Chinese Character Recognition of Vehicle License Plate Based on ALBP and Gabor Filters 基于ALBP和Gabor滤波器的车牌低分辨率汉字识别

2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.104

Ye Wang, Honggang Zhang, Xu Fang, Jun Guo

引用次数: 20

On Small Sample Prediction of Financial Crisis 金融危机的小样本预测研究

2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.102

Sankha Pallab Saha

{"title":"On Small Sample Prediction of Financial Crisis","authors":"Sankha Pallab Saha","doi":"10.1109/ICAPR.2009.102","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.102","url":null,"abstract":"Prediction of financial crisis is a challenging problem in financial research. On the basis of the information provided by financial statements, companies are usually classified into two groups, e.g., the groups of solvent and insolvent companies. Linear discriminant analysis (LDA), logistic regression and artificial neural network (ANN) are the most common statistical tools used for this classification. LDA and logistic regression separate the two groups using a hyperplane, and they provide good lower dimensional view of class separability. However, these methods are not robust against outliers and they also get affected by deviations from underlying model assumptions. Moreover, if the number of observations is small compared to the dimension of the measurement vector, these classical methods may lead to poor classification. On the contrary, ANN is more flexible and does not make any assumption about the population structure. But, it separates the competing populations using a complex surface. So, we sacrifice the lower dimensional view and the interpretability of the result, which are often the major concern in financial analysis. In this article, we propose to use a semiparametric method which preserves the interpretability and the lower dimensional view of class separability, but at the same time it is robust against outliers and capable to work well in high dimension and low sample size set up. We use two real life financial data sets to show the utility of this semiparametric method.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132105259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Cast Shadow Removal Using Time and Exposure Varying Images 投影去除使用时间和曝光变化的图像

2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.105

Pankaj Rajan, Wei Yan

引用次数: 2

Separation of Foreground Text from Complex Background in Color Document Images 彩色文档图像中前景文本与复杂背景的分离

2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.26

S. Nirmala, P. Nagabhushan

{"title":"Separation of Foreground Text from Complex Background in Color Document Images","authors":"S. Nirmala, P. Nagabhushan","doi":"10.1109/ICAPR.2009.26","DOIUrl":"https://doi.org/10.1109/ICAPR.2009.26","url":null,"abstract":"Reading of the foreground text is difficult in documents having multi colored complex background. Automatic foreground text separation in such document images is very much essential for smooth reading of the document contents. In this paper we propose a hybrid approach which combines connected component analysis and an unsupervised thresholding for separation of text from the complex background. The proposed approach identifies the candidate text regions based on edge detection followed by a connected component analysis. Because of background complexity it is also possible that a non text region may be identified as a text region. To overcome this problem we extract texture features of connected components and analyze the feature values. Finally the threshold value for each detected text region is derived automatically from the data of corresponding image region to perform foreground separation. The proposed approach can handle document images with varying background of multiple colors. Also it can handle foreground text of any color, font and size. Experimental results show that the proposed algorithm detects on an average 97.8% of text regions in the source document. Readability of the extracted foreground text is illustrated through OCRing.","PeriodicalId":443926,"journal":{"name":"2009 Seventh International Conference on Advances in Pattern Recognition","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117082996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 23

Improving Accuracy of Discovered Knowledge through Direct Interaction and Cohesion-based Framework: A Study in Cell Cycle Data of Yeast 通过直接相互作用和基于内聚的框架提高发现知识的准确性:酵母细胞周期数据的研究

2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.90

R. Bhattacharyya

引用次数: 0

Parallel Point Symmetry Based Clustering for Gene Microarray Data 基于平行点对称的基因微阵列数据聚类

2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.40

Anasua Sarkar, U. Maulik

引用次数: 11

Saving Electrical Power in a Surveillance Environment 在监控环境中节约电力

2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.38

Souvik Sen, A. Das, S. Chowdhury

引用次数: 3

Face Tracking Based on 3D Positional Hypothesis 基于三维位置假设的人脸跟踪

2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.32

Yuzuko Utsumi, Y. Iwai, M. Yachida

引用次数: 0

Best Basis Selection Using Singular Value Decomposition 基于奇异值分解的最佳基选择

2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.13

Esakkirajan Sankaralingam, Veerakumar Thangaraj, P. Navaneethan

引用次数: 6

Adaptive Objects Tracking by Using Statistical Features Shape Modeling and Histogram Analysis 基于统计特征、形状建模和直方图分析的自适应目标跟踪

2009 Seventh International Conference on Advances in Pattern Recognition Pub Date : 2009-02-04 DOI: 10.1109/ICAPR.2009.106

C. Spampinato

引用次数: 10