Differentiation between alphabetic and numeric data using NN ensembles

Presents an approach to differentiating handwritten alphabetic words from numeric strings, which is motivated by an application in a real-life bank cheque processing system. Neural networks are first considered with the focus on effective feature extraction and architecture selection. The combination of networks is then implemented to achieve highly reliable and accurate results.