Title :
Comparative Classifier Aggregation
Author :
Abdulkader, Ahmad ; Drakopoulos, John A. ; Zhang, Qi
Author_Institution :
Tablet PC Handwriting Recognition Group, Microsoft Corp., Redmond, WA
Abstract :
Comparative neural networks are a new kind of neural networks that can be used to compare two or more items given a set of context features. They compare two items at a time indicating the one that matches the context features better. Consequently, any sorting algorithm, coupled with such a neural comparator, can sort any set of items. Although applications include ink segmentation (for handwriting recognition purposes) and Web page ranking, our emphasis on this paper is on classifier aggregation and, in particular, the integration of our standard handwriting recognizers with a user personalization database that consists of user samples
Keywords :
handwriting recognition; handwritten character recognition; neural nets; pattern classification; comparative classifier aggregation; comparative neural network; context feature matching; handwriting recognition; handwriting recognizer; item comparison; item sorting; neural comparator; user personalization database; Aggregates; Convergence; Databases; Handwriting recognition; Ink; Neural networks; Pattern recognition; Sorting; Training data; Web pages;
Conference_Titel :
Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2521-0
DOI :
10.1109/ICPR.2006.388