DocumentCode :
2635754
Title :
Knowledge modeling methods in the framework of evidence theory: an experimental comparison for melanoma detection
Author :
Lefevre, Eric ; Colot, Olivier ; Vannoorenberghe, Patrick ; De Brucq, Denis
Author_Institution :
PSI, Rouen Univ., Mont-Saint-Aignan, France
Volume :
4
fYear :
2000
fDate :
2000
Firstpage :
2806
Abstract :
The Dempster-Shafer theory, or evidence theory, is used in different fields such as data fusion, regression or classification. Within the framework of this theory, uncertain and imprecise data are represented using belief functions. Data fusion operators as well as the decision rule of this theory were largely developed and formalized. The aim of the paper is to present modeling methods of knowledge for the initialization of belief functions. Moreover, an experimental comparison of these different modeling methods on real data extracted from images of dermatological lesions is presented
Keywords :
belief maintenance; cancer; inference mechanisms; medical expert systems; skin; uncertainty handling; Dempster-Shafer theory; belief functions; data fusion; data fusion operators; decision rule; dermatological lesion images; evidence theory; imprecise data; knowledge modeling methods; melanoma detection; modeling methods; real data; Attenuation; Data analysis; Data mining; Equations; Lesions; Malignant tumors; Probability distribution; Reliability theory; Upper bound;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 2000 IEEE International Conference on
Conference_Location :
Nashville, TN
ISSN :
1062-922X
Print_ISBN :
0-7803-6583-6
Type :
conf
DOI :
10.1109/ICSMC.2000.884422
Filename :
884422
Link To Document :
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