Title :
On multiple classifier systems for pattern recognition
Author :
Ho, Tin Kam ; Hull, Jonathan J. ; Srihari, Sargur N.
Author_Institution :
Center for Document Anal. & Recognition, State Univ. of New York, Buffalo, NY, USA
fDate :
30 Aug-3 Sep 1992
Abstract :
Difficult pattern recognition problems involving large class sets and noisy input can be solved by a multiple classifier system, which allows simultaneous use of arbitrary feature descriptors and classification procedures. Independent decisions by each classifier can be combined by methods of the highest rank, Borda count, and logistic regression, resulting in substantial improvement in overall correctness
Keywords :
image recognition; Borda count; arbitrary feature descriptors; highest rank method; logistic regression; multiple classifier systems; pattern recognition; Logistics; Pattern analysis; Pattern recognition; Sorting; Text analysis; Tin; Working environment noise;
Conference_Titel :
Pattern Recognition, 1992. Vol.II. Conference B: Pattern Recognition Methodology and Systems, Proceedings., 11th IAPR International Conference on
Conference_Location :
The Hague
Print_ISBN :
0-8186-2915-0
DOI :
10.1109/ICPR.1992.201727
