This paper presents a method for the syntactic parsing of Hungarian natural language texts using a machine learning approach. This method learns tree patterns with various phrase types described by regular expressions from an annotated corpus. The PGS algorithm, an improved version of the RGLearn method, is developed and applied as a classifier in classifier combination schemas. Experiments sho...

Hand gesture recognition is a topic in artificial intelligence and computer vision with the goal to automatically interpret human hand gestures via some algorithms. Notice that it is a difficult classification task for which only one simple classifier cannot achieve satisfactory performance; several classifier combination techniques are employed in this paper to handle this specific problem. Ba...

In the therapy of the hearing impaired one of the key problems is how to deal with the lack of proper auditive feedback which impedes the development of intelligible speech. The effectiveness of the therapy relies heavily on accurate phoneme recognition [?,?,?]. Because of the environmental difficulties, simple recognition algorithms may have a weak classification performance, so various techni...

An ensemble of classifiers consists of a set of individually trained classifiers whose predictions are combined when classifying new instances. The resulting ensemble is generally more accurate than the individual classifiers it consists of. In particular, one of the most popular ensemble methods, the Boosting approach, improves the predictive performance of weak classifiers, which can achieve ...

This study presents a theoretical investigation of the rankbased multiple classifier decision problem for closed-set pattern identification. The problem of combining the decisions of more than one classifiers with raw outputs in the form of candidate class rankings is considered and formulated as a general discrete optimization problem with an objective function based on the total probability o...

Mobile mapping of environment information from a moving platform plays an important role in the automatic acquisition of GIS (Geographic Information Systems). The extraction of railway infrastructure from video frames captured on a driving train requires a robust visual object detection system that provides both high localization accuracy and the capability to cope with uncertain information. T...

This paper presents an approach to learning from noisy data that views the problem as one of reasoning under uncertainty, where prior knowledge of the noise process is applied to compute a pos-teriori probabilities over the hypothesis space. In preliminary experiments this maximum a posteri-ori (MAP) approach exhibits a learning rate advantage over the C4.5 algorithm that is statistically signi...

The performance of multiple classifier systems varies with the performance of component classifiers as well as the method of combination. In this paper, informationtheoretic methods are proposed for constructing multiple classifier systems, provided that the number of component classifiers is constrained in advance. These proposed methods are applied to a classifier pool and examine the possibl...

In this work, we make a contribution to natural speech dialogue act detection. We focus our attention on the dialogue act classification using a Bayesian approach. Our classifier is tested on two corpora, the Switchboard and the Basurde tasks. A combination of a naive Bayes classifier and n-grams is used. The impact of different smoothing methods (Laplace and Witten Bell) and n-grams in classif...

Constructing a precise classifier is an important issue in pattern recognition task. Combination the decision of several competing classifiers to achieve improved classification accuracy has become interested in many research areas. In this study, Artificial Immune System (AIS) as an effective artificial intelligence technique was used for designing of several efficient classifiers. Combination...