Combination of Three Classifiers with Different Architectures for Handwritten Word Recognition
Simon Günter, Horst Bunke · 2004
The study of multiple classifier systems has become an area of intensive research in pattern recognition recently. Also in handwriting recognition, systems combining several classifiers have been investigated. In this paper the combination of three classifiers for handwritten word recognition with different architectures is studied. In addition a new ensemble method working with several base classifiers is applied and the results of the ensemble method are compared to the results of the combination of the three classifiers. In the experiments a large-scale handwritten word recognition task is considered.