Title :
Neural versus syntactic recognition of handwritten numerals
Author :
Veloso, Luciana R. ; De Carvalho, João Marques
Author_Institution :
Dept. de Engenharia Electrica, UFPB, Campina Grande, Brazil
Abstract :
This work concerns the analysis, implementation and evaluation of three different methods for handwritten numerical character recognition. The first approach uses a classifier based on syntactical analysis by decision tree. The other two methods consist of: (a) a conventional feedforward multilayer neural network; and (b) a recurrent neural network, for which the elements of the output layer are all interconnected. The CENPARMI database was utilized for evaluation of the systems
Keywords :
computational linguistics; decision trees; feedforward neural nets; handwritten character recognition; image recognition; recurrent neural nets; CENPARMI database; conventional feedforward multilayer neural network; decision tree; handwritten numerals; handwritten numerical character recognition; neural recognition; output layer; recurrent neural network; syntactic recognition; syntactical analysis; Character recognition; Feedforward neural networks; Handwriting recognition; Machine intelligence; Multi-layer neural network; Neural networks; Postal services; Shape; Spatial databases; System testing;
Conference_Titel :
Document Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference on
Conference_Location :
Bangalore
Print_ISBN :
0-7695-0318-7
DOI :
10.1109/ICDAR.1999.791767
