In this work, we proposes a novel method for mining frequent disjunctive patterns on single data sequence. For this purpose, we introduce a sophisticated measure that satisfies anti-monotonicity, by which we can discu...
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ISBN:
(纸本)3540269231
In this work, we proposes a novel method for mining frequent disjunctive patterns on single data sequence. For this purpose, we introduce a sophisticated measure that satisfies anti-monotonicity, by which we can discuss efficient mining algorithm based on APRIORI. We discuss some experimental results.
Steering an autonomous vehicle requires the permanent adaptation of behavior in relation to the various situations the vehicle is in. this paper describes a research which implements such adaptation and optimization b...
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Support Vector machines have received considerable attention from the patternrecognition community in recent years. they have been applied to various classical recognition problems achieving comparable or even superi...
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ISBN:
(纸本)3540269231
Support Vector machines have received considerable attention from the patternrecognition community in recent years. they have been applied to various classical recognition problems achieving comparable or even superior results to classifiers such as neural networks. We investigate the application of Support Vector machines (SVMs) to the problem of road recognition from remotely sensed images using edge-based features. We present very encouraging results from our experiments, which are comparable to decision tree and neural network classifiers.
this paper proposes an unsupervised algorithm for learning a finite Dirichlet mixture model. An important part of the unsupervised learning problem is determiningthe number of clusters which best describe the data. W...
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ISBN:
(纸本)3540269231
this paper proposes an unsupervised algorithm for learning a finite Dirichlet mixture model. An important part of the unsupervised learning problem is determiningthe number of clusters which best describe the data. We consider here the application of the Minimum Message length (MML) principle to determine the number of clusters. the Model is compared with results obtained by other selection criteria (AIC, MDL, MMDL, PC and a Bayesian method). the proposed method is validated by synthetic data and summarization of texture image database.
Feature selection method for text classification based on information gain ranking, improved by removing redundant terms using mutual information measure and inclusion index, is proposed. We report an experiment to st...
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the work presented in this paper is part of the cooperative research project AUTO-OPT carried out by twelve partners from the automotive industries. One major work package concerns the application of datamining metho...
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In this paper we present a method to cluster large datasets that change over time using incremental learning techniques. the approach is based on the dynamic representation of clusters that involves the use of two set...
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Face recognition is a challenging visual classification task, especially when the lighting conditions can not be controlled. In this paper, we present an automatic face recognition system in the near infrared (IR) spe...
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the task of extracting knowledge from text is an important research problem for information processing and document understanding. Approaches to capture the semantics of picture objects in documents constitute subject...
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