Abstract In many Pattern Recognition applications, the achievement of acceptable
recognition rates is conditioned by the large pattern variability, whose distribution cannot be …

This paper investigates the use of multiple classifier methods for offline handwritten text line
recognition. To obtain ensembles of recognisers we implement a random feature subspace …

Power systems evolve all the time and increase in renewable resources and fluctuating
electricity usage obligates renewal of power systems. The supply security and flexibility of …

In this paper we propose a general framework for analysing the diversity of ensembles of
word sequence recognition systems. The goal of the framework is to enable the application …

In this paper, an ensemble classifier, namely RotaSVM, is proposed that uses recently
developed rotational feature selection approach and Support Vector Machine classifier …

This paper describes recent work on ensemble methods for offline handwritten text line
recognition. We discuss techniques to build ensembles of recognizers by systematically …

Introduction Classifier ensembles have been one of the main topics of interest in the neural
networks, machine learning and pattern recognition communities during the past fifteen …

Multiple classifier systems are a well proven and tested instrument for enhancing the
recognition accuracy in statistical pattern recognition problems. However, there has been …