An efficient low-level word image representation plays a crucial role in general cursive word recognition. this paper proposes a novel representation scheme, where a word image can be represented as two sequences of f...
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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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Several cost-sensitive boosting algorithms have been reported as effective methods in dealing with class imbalance problem. Misclassification costs, which reflect the different level of class identification importance...
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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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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 accuracy of the rules produced by a concept learning system can be hindered by the presence of errors in the data. Although these errors are most commonly attributed to random noise, there also exist "ill-def...
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ISBN:
(纸本)3540298967
the accuracy of the rules produced by a concept learning system can be hindered by the presence of errors in the data. Although these errors are most commonly attributed to random noise, there also exist "ill-defined" attributes that are too general or too specific that can produce systematic classification errors. We present a computer program called Newton which uses the fact that ill-defined attributes create an ordered error pattern among the instances to compute hypotheses explaining the classification errors of a concept in terms of too general or too specific attributes. Extensive empirical testing shows that Newton identifies such attributes with a prediction rate over 95%.
this paper uses a set of 3D geometric measures withthe purpose of characterizing lung nodules as malignant or benign. Based on a sample of 36 nodules, 29 benign and 7 malignant, these measures are analyzed with a tec...
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Recently applying artificial intelligence, machinelearning and data mining techniques to intrusion detection system are increasing. But most of researches are focused on improving the performance of classifier. Selec...
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When we mine information for knowledge on a whole data streams it's necessary to cope with uncertainty as only a part of the stream is available. We introduce a stastistical technique, independant from the used al...
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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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