Title :
Multiple novelty input neural networks for unconstrained handwritten numeral recognition
Author :
Lim, Kil-Taek ; Chien, Sung-II ; Kang, Soon-Ju
Author_Institution :
Dept. of Electron., Kyungpook Nat. Univ., Taegu, South Korea
fDate :
5/28/1998 12:00:00 AM
Abstract :
Multiple novelty input neural networks have been presented. It is shown that this method produces relatively good recognition accuracy for an unconstrained handwritten numeral database
Keywords :
neural nets; handwritten numeral database; multiple novelty input neural networks; recognition accuracy; unconstrained handwritten numeral recognition;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19980769
