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Data Crawlers for Simple Optical Character Recognition Dan Ashlock
 

Summary: Data Crawlers for Simple Optical Character Recognition
Dan Ashlock
Mathematics and Complex Adaptive Systems
Iowa State University
Ames, IA 50011
danwell@iastate.edu
Abstract
Many genetic programming systems have been de-
signed to exploit the use of state information in an
indirect fashion. In this article we apply a genetic pro-
gramming technique that directly incorporates state
information to a collection of related optical charac-
ter recognition tasks. Our recognizers are coded as
GP-Automata, finite state machines modified by asso-
ciating a function, stored as a parse tree, with each
state. These functions are called deciders and serve
to extract information from a high bandwidth input
to drive finite state transitions. The GP-Automata
make iterated decisions, requesting additional data in
an adaptive fashion. This iterated data processing is

  

Source: Ashlock, Dan - Department of Mathematics and Statistics, University of Guelph

 

Collections: Mathematics