History


Please fill in your query. A complete syntax description you will find on the General Help page.
Combining classifiers in face recognition. (Chinese)
J. Shanghai Jiaotong Univ. (Chin. Ed.) 35, No.2, 173-176 (2001).
Summary: This paper discussed the familiar combination methods like sum, product, median and vote rules according to the Bayesian theory and pointed out their weakpoints. Inspired by election in the real world it improved the majority vote rule: different classifiers have different “loud voice” which means different weights; a “second candidate” is added; the difference reliability of the first and the second candidate is used to give “bonus votes”. Finally, a face recognition experiment using ORL (Olivetti and Oracle Research Lab’s) face image database is presented. Eigenface, synergetic algorithm and auto-associative neural network a combined. The result shows that the recognition rate of the new method is better than those of old ones.
WorldCat.org
Valid XHTML 1.0 Transitional Valid CSS!