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2010 International Conference of Soft Computing and Pattern Recognition最新文献

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Static task graph scheduling using learner Genetic Algorithm 基于学习遗传算法的静态任务图调度
2010 International Conference of Soft Computing and Pattern Recognition Pub Date : 2010-12-01 DOI: 10.1109/SOCPAR.2010.5686731
Habib Motee Ghader, K. Fakhr, Mahmood Javadi, Gisou Bakhshzadeh
{"title":"Static task graph scheduling using learner Genetic Algorithm","authors":"Habib Motee Ghader, K. Fakhr, Mahmood Javadi, Gisou Bakhshzadeh","doi":"10.1109/SOCPAR.2010.5686731","DOIUrl":"https://doi.org/10.1109/SOCPAR.2010.5686731","url":null,"abstract":"Task graph scheduling is one of the NP-Hard problems. So many classic and non-classic methods are proposed for solution of this problem. One of the crucial methods that, applied for solving this problem is Genetic Algorithm. In this paper we propose a new algorithm that named Learner Genetic Algorithm (LGA). Our proposed algorithm based on Genetic Algorithm, but in new proposed algorithm the Learning Process is attached for Genetic Algorithm. The scheduling resulted from applying our proposed algorithm to some benchmark task graphs are compared with the existing ones.","PeriodicalId":397384,"journal":{"name":"2010 International Conference of Soft Computing and Pattern Recognition","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127206032","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: 2
Investigating analysis of speech content through text classification 通过文本分类研究语音内容分析
2010 International Conference of Soft Computing and Pattern Recognition Pub Date : 2010-12-01 DOI: 10.1109/SOCPAR.2010.5686000
Souraya Ezzat, N. E. Gayar, M. Moustafa
{"title":"Investigating analysis of speech content through text classification","authors":"Souraya Ezzat, N. E. Gayar, M. Moustafa","doi":"10.1109/SOCPAR.2010.5686000","DOIUrl":"https://doi.org/10.1109/SOCPAR.2010.5686000","url":null,"abstract":"The field of Text Mining has evolved over the past years to analyze textual resources. However, it can be used in several other applications. In this research, we are particularly interested in performing text mining techniques on audio materials after translating them into texts in order to detect the speakers' emotions. We describe our overall methodology and present our experimental results. In particular, we focus on the different features selection and classification methods used. Our results show interesting conclusions opening up new horizons in the field, and suggest an emergence of promising future work yet to be discovered.","PeriodicalId":397384,"journal":{"name":"2010 International Conference of Soft Computing and Pattern Recognition","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125468960","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: 8
Image annotation using fuzzy knowledge representation scheme 基于模糊知识表示方案的图像标注
2010 International Conference of Soft Computing and Pattern Recognition Pub Date : 2010-12-01 DOI: 10.1109/SOCPAR.2010.5686618
Marina Ivasic-Kos, I. Ipšić, S. Ribaric
{"title":"Image annotation using fuzzy knowledge representation scheme","authors":"Marina Ivasic-Kos, I. Ipšić, S. Ribaric","doi":"10.1109/SOCPAR.2010.5686618","DOIUrl":"https://doi.org/10.1109/SOCPAR.2010.5686618","url":null,"abstract":"In order to exploit the massive image information and to handle overload, techniques for analysing image content to facilitate indexing and retrieval of images have emerged. In this paper, a semantic image content analysis framework based on Fuzzy Petri Net is presented. Knowledge scheme is used to define more general and complex semantic concepts and their relations in the context of the examined outdoor domain. A formal description of hierarchical and spatial relationships among concepts from the outdoor image domain is described. The automatic image annotation procedure based on fuzzy recognition algorithm, that maps high-level semantics to image, is presented.","PeriodicalId":397384,"journal":{"name":"2010 International Conference of Soft Computing and Pattern Recognition","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114237395","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: 4
Breast cancer diagnostic system using Symbiotic Adaptive Neuro-evolution (SANE) 基于共生自适应神经进化(SANE)的乳腺癌诊断系统
2010 International Conference of Soft Computing and Pattern Recognition Pub Date : 2010-12-01 DOI: 10.1109/SOCPAR.2010.5686161
R. Janghel, A. Shukla, R. Tiwari, R. Kala
{"title":"Breast cancer diagnostic system using Symbiotic Adaptive Neuro-evolution (SANE)","authors":"R. Janghel, A. Shukla, R. Tiwari, R. Kala","doi":"10.1109/SOCPAR.2010.5686161","DOIUrl":"https://doi.org/10.1109/SOCPAR.2010.5686161","url":null,"abstract":"Breast cancer is the second leading cause of cancer deaths in women worldwide and occurs in nearly one out of eight women. In this paper we develop a hybrid intelligent system for diagnosis, prognosis and prediction for breast cancer using SANE (Symbiotic, Adaptive Neuro-evolution) and compare with ensemble ANN, modular neural network, fixed architecture evolutionary neural network (F-ENN) and Variable Architecture evolutionary neural network (V-ENN). While the monolithic neural and fuzzy systems have been extensively used for diagnosis, the individual limitations of the various models put a great threshold on prediction accuracies, which may be overcome with the use of SANE. The SANE system coevolves a population of neurons that cooperate to form a functioning neural network. Breast cancer database from the University of Wisconsin available at UCI Machine Learning Repository is used for conducting experimental work.","PeriodicalId":397384,"journal":{"name":"2010 International Conference of Soft Computing and Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115816144","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: 12
Classification by means of fuzzy analogy-related proportions — A preliminary report 用模糊类比相关比例进行分类。初步报告
2010 International Conference of Soft Computing and Pattern Recognition Pub Date : 2010-12-01 DOI: 10.1109/SOCPAR.2010.5686636
H. Prade, G. Richard, Bing Yao
{"title":"Classification by means of fuzzy analogy-related proportions — A preliminary report","authors":"H. Prade, G. Richard, Bing Yao","doi":"10.1109/SOCPAR.2010.5686636","DOIUrl":"https://doi.org/10.1109/SOCPAR.2010.5686636","url":null,"abstract":"Boolean logic interpretations, as well as multiple-valued logic extensions, have been recently proposed for analogical proportions (i.e. statements of the form “a is to b as c is to d”), and for two other related formal proportions named reverse analogy (“what a is to b is the reverse of what c is to d”), and paralogy (“what a and b have in common c and d have it also”). These proportions relate items a, b, c, and d on the basis of their differences, or of their similarities. This may provide a basis for proposing a plausible classification for an object d described in terms of a set of features, on the basis of three other already classified objects described on the same features, considering that if some proportion holds for a sufficiently large number of features, it may hold on the allocation of the classes as well. This is the basis of a classification method which is tested on machine learning benchmarks for binary or multiple class problems with objects that have numerical features.","PeriodicalId":397384,"journal":{"name":"2010 International Conference of Soft Computing and Pattern Recognition","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134216718","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: 12
When classifier selection meets information theory: A unifying view 当分类器选择遇到信息论:一个统一的观点
2010 International Conference of Soft Computing and Pattern Recognition Pub Date : 2010-12-01 DOI: 10.1109/SOCPAR.2010.5686645
Mohamed Farouk Abdel Hady, F. Schwenker, G. Palm
{"title":"When classifier selection meets information theory: A unifying view","authors":"Mohamed Farouk Abdel Hady, F. Schwenker, G. Palm","doi":"10.1109/SOCPAR.2010.5686645","DOIUrl":"https://doi.org/10.1109/SOCPAR.2010.5686645","url":null,"abstract":"Classifier selection aims to reduce the size of an ensemble of classifiers in order to improve its efficiency and classification accuracy. Recently an information-theoretic view was presented for feature selection. It derives a space of possible selection criteria and show that several feature selection criteria in the literature are points within this continuous space. The contribution of this paper is to export this information-theoretic view to solve an open issue in ensemble learning which is classifier selection. We investigated a couple of information-theoretic selection criteria that are used to rank classifiers.","PeriodicalId":397384,"journal":{"name":"2010 International Conference of Soft Computing and Pattern Recognition","volume":"242 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131881428","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: 3
Profiling the power usage of industrial machinery by ANN 用人工神经网络分析工业机械的用电量
2010 International Conference of Soft Computing and Pattern Recognition Pub Date : 2010-12-01 DOI: 10.1109/SOCPAR.2010.5686621
S. Ierace, Pasquale Marinaro, Pasquale Tatavitto, L. Troiano
{"title":"Profiling the power usage of industrial machinery by ANN","authors":"S. Ierace, Pasquale Marinaro, Pasquale Tatavitto, L. Troiano","doi":"10.1109/SOCPAR.2010.5686621","DOIUrl":"https://doi.org/10.1109/SOCPAR.2010.5686621","url":null,"abstract":"Neural networks can provide an effective way for profiling a plant, if conditions are accurately sampled and data properly collected. In this paper we investigate such an approach, considering a textile finishing machinery named rameuse as experimental context.","PeriodicalId":397384,"journal":{"name":"2010 International Conference of Soft Computing and Pattern Recognition","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132446131","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: 8
Mapping loops onto Coarse-Grained Reconfigurable Architectures using Particle Swarm Optimization 使用粒子群优化将循环映射到粗粒度可重构架构上
2010 International Conference of Soft Computing and Pattern Recognition Pub Date : 2010-12-01 DOI: 10.1109/SOCPAR.2010.5685969
Rani Gnanaolivu, T. Norvell, R. Venkatesan
{"title":"Mapping loops onto Coarse-Grained Reconfigurable Architectures using Particle Swarm Optimization","authors":"Rani Gnanaolivu, T. Norvell, R. Venkatesan","doi":"10.1109/SOCPAR.2010.5685969","DOIUrl":"https://doi.org/10.1109/SOCPAR.2010.5685969","url":null,"abstract":"Coarse-Grained Reconfigurable Architectures (CGRAs) have gained currency in recent years due to their abundant parallelism and flexibility. To utilize the abundant parallelism found in CGRAs, we propose a fast and efficient Modulo-Constrained Hybrid Particle Swarm Optimization (MCHPSO) scheduling algorithm to exploit loop level parallelism in applications. PSO has been proved to be successful in many applications in continuous optimization problems. In this paper, we show that PSO is capable of software pipelining loops by overlapping placement, scheduling and routing of successive loop iterations and executing them in parallel. Our proposed algorithm has been experimentally validated on various DSP benchmarks under two different architecture configurations. These experiments indicate that the proposed MCHPSO algorithm can find schedules with small initiation intervals within a reasonable amount of time. PSO is thus a promising alternative for obtaining near optimal solutions to this NP-hard scheduling problem.","PeriodicalId":397384,"journal":{"name":"2010 International Conference of Soft Computing and Pattern Recognition","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116488051","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: 12
An uncertain database model and a query algebra based on possibilistic certainty 一种不确定数据库模型及基于可能性确定性的查询代数
2010 International Conference of Soft Computing and Pattern Recognition Pub Date : 2010-12-01 DOI: 10.1109/SOCPAR.2010.5686430
P. Bosc, O. Pivert, H. Prade
{"title":"An uncertain database model and a query algebra based on possibilistic certainty","authors":"P. Bosc, O. Pivert, H. Prade","doi":"10.1109/SOCPAR.2010.5686430","DOIUrl":"https://doi.org/10.1109/SOCPAR.2010.5686430","url":null,"abstract":"In this paper, we consider relational databases containing uncertain attribute values, in the situation where some knowledge is available about the more or less certain value (or disjunction of values) that a given attribute in a tuple can take. We propose a possibility-theory-based model suited to this context and extend the operators of relational algebra in order to handle such relations in a “compact” thus efficient way. It is shown that the proposed model is a strong representation system for the whole relational algebra. An important result is that the data complexity associated with the extended operators in this context is the same as in the classical database case, which makes the approach highly scalable.","PeriodicalId":397384,"journal":{"name":"2010 International Conference of Soft Computing and Pattern Recognition","volume":"79 16","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120897310","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: 10
Similarity learning in nearest neighbor, positive semi-definitiveness and RELIEF algorithm 最近邻相似性学习、正半确定性与RELIEF算法
2010 International Conference of Soft Computing and Pattern Recognition Pub Date : 2010-12-01 DOI: 10.1109/SOCPAR.2010.5686633
A. M. Qamar, Éric Gaussier
{"title":"Similarity learning in nearest neighbor, positive semi-definitiveness and RELIEF algorithm","authors":"A. M. Qamar, Éric Gaussier","doi":"10.1109/SOCPAR.2010.5686633","DOIUrl":"https://doi.org/10.1109/SOCPAR.2010.5686633","url":null,"abstract":"In this paper, we develop a similarity learning version of RELIEF algorithm, called RBS-PSD (for RELIEF-Based Similarity learning) where the learned similarity matrix is projected onto the set of positive, semi-definite matrices. Unfortunately, this algorithm does not perform very well in practice since it does not try to optimize the leave-one-out error or the 0–1 loss. This motivated us to develop its stricter version, called sRBS-PSD, which aims at reducing a cost function closer to the 0–1 loss. In the case of sRBS-PSD also, the similarity matrix is projected onto the set of positive, semi-definite matrices. Experiments reveal that this projection improves the performance for all of these algorithms. Furthermore, it has been shown that sRBS-PSD outperforms its counterparts for majority of the data sets.","PeriodicalId":397384,"journal":{"name":"2010 International Conference of Soft Computing and Pattern Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129122299","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
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