DocumentCode
2489750
Title
Incremental classification of invoice documents
Author
Hamza, Hatem ; Belaïd, Yolande ; Belaïd, Abdel ; Chaudhuri, Bidyut B.
Author_Institution
ITESOFT
fYear
2008
fDate
8-11 Dec. 2008
Firstpage
1
Lastpage
4
Abstract
This paper deals with incremental classification and its particular application to invoice classification. An improved version of an already existant incremental neural network called IGNG (incremental growing neural gas) is used for this purpose. This neural network tries to cover the space of data by adding or deleting neurons as data is fed to the system. The improved version of the IGNG, called I2GNG used local thresholds in order to create or delete neurons. Applied on invoice documents represented with graphs, I2GNG shows a recognition rate of 97.63%.
Keywords
document handling; learning (artificial intelligence); neural nets; pattern classification; incremental classification; incremental growing neural gas; incremental neural network; invoice documents; Databases; Equations; Image segmentation; Machine learning; Neural networks; Neurons; Self organizing feature maps; Tree graphs;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location
Tampa, FL
ISSN
1051-4651
Print_ISBN
978-1-4244-2174-9
Electronic_ISBN
1051-4651
Type
conf
DOI
10.1109/ICPR.2008.4761832
Filename
4761832
Link To Document