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检索条件"任意字段=3rd IAPR Workshop on Artificial Neural Networks in Pattern Recognition"
274 条 记 录,以下是201-210 订阅
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Ammonium estimation in a biological wastewater plant using feedforward neural networks
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2nd iapr workshop on artificial neural networks in pattern recognition
作者: Garcia, Hilario Lopez Gonzalez, Ivan Machon Univ Oviedo Escuela Politecn Super Ingn Dept Ingn Elect Elect Computadores & Sistemas Edif Dept Zona Oeste 2 Asturias 33204 Spain
Mathematical models are normally used to calculate the component concentrations in biological wastewater treatment. However, this work deals with the wastewater from a coke plant and it implies inhibition effects betw... 详细信息
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Hierarchical neural networks utilising Dempster-Shafer evidence theory
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2nd iapr workshop on artificial neural networks in pattern recognition
作者: Fay, Rebecca Schwenker, Friedhelm Thiel, Christian Palm, Guenther Univ Ulm Dept Neural Informat Proc D-89069 Ulm Germany
Hierarchical neural networks show many benefits when employed for classification problems even when only simple methods analogous,to decision trees are used to retrieve the classification result. More complex ways of ... 详细信息
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Combining MF networks:: A comparison among statistical methods and Stacked Generalization
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2nd iapr workshop on artificial neural networks in pattern recognition
作者: Torres-Sospedra, Joaquin Hernandez-Espinosa, Carlos Fernandez-Redondo, Mercedes Univ Jaume 1 Dept Ingn & Ciencia Computadores Castellon de La Plana 12071 Spain
The two key factors to design an ensemble of neural networks are how to train the individual networks and how to combine the different outputs to get a single output. In this paper we focus on the combination module. ... 详细信息
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On the effects of constraints in semi-supervised hierarchical clustering
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2nd iapr workshop on artificial neural networks in pattern recognition
作者: Kestler, Hans A. Kraus, Johann M. Palm, Guenther Schwenker, Friedhelm Univ Ulm Dept Neural Informat Proc D-89069 Ulm Germany Univ Hosp Ulm Dept Internal Med 1 D-89081 Ulm Germany
We explore the use of constraints with divisive hierarchical clustering. We mention some considerations on the effects of the inclusion of constraints into the hierarchical clustering process. Furthermore, we introduc... 详细信息
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Supervised batch neural gas
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2nd iapr workshop on artificial neural networks in pattern recognition
作者: Hammer, Barbara Hasenfuss, Alexander Schleif, Frank-Michael Villmann, Thomas Tech Univ Clausthal Inst Comp Sci D-3392 Clausthal Zellerfeld Germany Univ Leipzig Inst Comp Sci D-7010 Leipzig Germany Univ Leipzig Clin Psychotherapy D-7010 Leipzig Germany
Recently, two extensions of neural gas have been proposed: a fast batch version of neural gas for data given in advance, and extensions of neural gas to learn a (possibly fuzzy) supervised classification. Here we prop... 详细信息
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Fuzzy labeled self-organizing map with label-adjusted prototypes
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2nd iapr workshop on artificial neural networks in pattern recognition
作者: Villmann, Thomas Seiffert, Udo Schleif, Frank-Michael Bruess, Cornelia Geweniger, Tina Hammer, Barbara Univ Leipzig Dept Med D-7010 Leipzig Germany IPK Gatersleben Pattern Recognit Grp Gatersleben Germany BRUKER Daltonik Leipzig Numer Toolbox Grp Leipzig Germany Univ Leipzig Inst Comp Sci D-7010 Leipzig Germany Tech Univ Clausthal Inst Comp Sci D-3392 Clausthal Zellerfeld Germany
We extend the self-organizing map (SOM) in the form as proposed by Heskes to a supervised fuzzy classification method. On the one hand, this leads to a robust classifier where efficient learning with fuzzy labeled or ... 详细信息
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Object detection and feature base learning with sparse convolutional neural networks
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2nd iapr workshop on artificial neural networks in pattern recognition
作者: Gepperth, Alexander R. T. Inst Neural Dynam D-44780 Bochum Germany
A new convolutional neural network model termed sparse convolutional neural network (SCNN) is presented and its usefulness for real-time object detection in gray-valued, monocular video sequences is demonstrated. SCNN... 详细信息
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Unsupervised feature selection for biomarker identification in chromatography and gene expression data
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2nd iapr workshop on artificial neural networks in pattern recognition
作者: Strickert, Marc Sreenivasulu, Nese Peterek, Silke Weschke, Winfriede Mock, Hans-Peter Seiffert, Udo Pattern Recognition Group Leibniz Institute of Plant Genetics and Crop Plant Research Gatersleben Germany Gene Expression Group Leibniz Institute of Plant Genetics and Crop Plant Research Gatersleben Germany Applied Biochemistry Leibniz Institute of Plant Genetics and Crop Plant Research Gatersleben Germany
A novel approach to feature selection from unlabeled vector data is presented. It is based on the reconstruction of original data relationships in an auxiliary space with either weighted or omitted features. Feature w... 详细信息
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Learning and feature selection using the set covering machine with data-dependent rays on gene expression profiles
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2nd iapr workshop on artificial neural networks in pattern recognition
作者: Kestler, Hans A. Lindner, Wolfgang Mueller, Andre Univ Ulm Neural Informat Proc D-89069 Ulm Germany Univ Hosp Ulm D-89081 Ulm Germany
Microarray technologies are increasingly being used in biological and medical sciences for high throughput analyses of genetic information on the genome, transcriptome and proteome levels. The differentiation between ... 详细信息
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A study of the robustness of KNN classifiers trained using soft labels
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2nd iapr workshop on artificial neural networks in pattern recognition
作者: El Gayar, Neamat Schwenker, Friedhelm Palm, Guenther Cairo Univ Fac Comp & Informat Giza 12613 Egypt Univ Ulm Dept Neural Informat Proc D-89069 Ulm Germany
Supervised learning models most commonly use crisp labels for classifier training. Crisp labels fail to capture the data characteristics when overlapping classes exist. In this work we attempt to compare between learn... 详细信息
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