2009 International Conference of Soft Computing and Pattern Recognition最新文献_第9页

An Ensemble of Deep Support Vector Machines for Image Categorization 图像分类的深度支持向量机集成

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.67

A. Abdullah, R. Veltkamp, M. Wiering

引用次数: 44

Quantum-Inspired Evolution Strategy 量子启发的进化策略

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.146

Hamid Izadinia, M. Ebadzadeh

引用次数: 4

Damageless Digital Watermarking by Machine Learning: A Method of Key Generation for Information Extraction Using Artificial Neural Networks 基于机器学习的无损数字水印:一种基于人工神经网络的信息提取密钥生成方法

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.109

Kensuke Naoe, H. Sasaki, Yoshiyasu Takefuji

引用次数: 1

Synergistic-ANN Recognizers for Monitoring and Diagnosis of Multivariate Process Shift Patterns 多变量过程移位模式监测与诊断的协同神经网络识别

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.61

I. Masood, A. Hassan

引用次数: 8

A Survey of Pattern Recognition Applications in Cancer Diagnosis 模式识别在癌症诊断中的应用综述

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.93

Amir Atapour-Abarghouei, A. Ghanizadeh, Saman Sinaie, S. Shamsuddin

引用次数: 9

Finite Difference Recursive Update on Decomposed RBF Networks for System Identification with Lost Packet 含丢包系统辨识的分解RBF网络有限差分递归更新

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.53

Nur Afny C. Andryani, V. Asirvadam, N. H. Hamid

{"title":"Finite Difference Recursive Update on Decomposed RBF Networks for System Identification with Lost Packet","authors":"Nur Afny C. Andryani, V. Asirvadam, N. H. Hamid","doi":"10.1109/SoCPaR.2009.53","DOIUrl":"https://doi.org/10.1109/SoCPaR.2009.53","url":null,"abstract":"Radial Basis Function networks (RBF) is one form of feed forward neural network architecture which is popular besides Multi Layer Preceptor (MLP). It is widely used in identifying a black box system. Finite Difference approach is used to improve the learning performance especially in the non-linear learning parameter update for identifying system with lost packet in online manner. Since initializing of non-linear learning’s parameters is crucial in RBF networks’ learning, some unsupervised learning methods such as, K-means clustering and Fuzzy C-means clustering are used besides random initialization. All the possible combination methods in the initialization and updating process try to improve the whole performance of the learning process in system identification with lost packet compared to Extreme Learning Machine as the latest improved learning method in RBF network. It can be shown that Finite difference approach with dynamic step size on Decomposed RBF network with Recursive Prediction Error for the non-linear parameter update with appropriate initialization method succeed to perform better performance compared to ELM.","PeriodicalId":284743,"journal":{"name":"2009 International Conference of Soft Computing and Pattern Recognition","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132925570","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: 0

Automatic Diagnostic System of Electrical Equipment Using Infrared Thermography 基于红外热像仪的电气设备自动诊断系统

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.41

Ying-Chieh Chou, L. Yao

引用次数: 114

Study of Data Fusion of AIS and Radar AIS与雷达数据融合研究

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.133

Liu Chang, Shi Xiaofei

引用次数: 10

Protein Fold Pattern Recognition Using Bayesian Ensemble of RBF Neural Networks 基于RBF神经网络贝叶斯集成的蛋白质折叠模式识别

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.91

H. Hashemi, A. Shakery, Mahdi Pakdaman Naeini

{"title":"Protein Fold Pattern Recognition Using Bayesian Ensemble of RBF Neural Networks","authors":"H. Hashemi, A. Shakery, Mahdi Pakdaman Naeini","doi":"10.1109/SoCPaR.2009.91","DOIUrl":"https://doi.org/10.1109/SoCPaR.2009.91","url":null,"abstract":"Protein fold pattern recognition has been one of the most challenging problems in biology during the last 40 years. Recently due to the vast improvement in machine learning and pattern recognition methods many computer scientists have applied these methods to solve this problem. However, protein folding problem is much more complicated than ordinary machine learning problems because of its natural complexity imposed by the high dimensionality of feature space and diversity of different protein fold classes. To deal with such a challenging problem, we use an ensemble classifier model by applying MLP and RBF Neural Networks and Bayesian ensemble method. Also we have used the Laplace estimation method in order to smooth confusion matrices of the base classifiers. Experimental results imply that RBF Neural Network holds better Correct Classification Rate (CCR) compared to other common classification methods such as MLP networks. Our experiments also show that the Bayesian fusion method can improve the correct classification rate of proteins up to 20% with the final CCR of 59% by reducing both bias and variance error of the RBF classifiers, on a benchmark dataset containing 27 SCOP folds.","PeriodicalId":284743,"journal":{"name":"2009 International Conference of Soft Computing and Pattern Recognition","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113982724","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: 22

The Inquiry and Page Procedure in Bluetooth Connection 蓝牙连接中的查询和页面程序

2009 International Conference of Soft Computing and Pattern Recognition Pub Date : 2009-12-04 DOI: 10.1109/SoCPaR.2009.52

T. Thamrin, S. Shahrin

引用次数: 4