Title :
Fuzzy learning in vicissitudinous environments
Author :
Dasarathy, Belur V.
Author_Institution :
Dynetics Inc., Huntsville, AL, USA
fDate :
30 Aug-3 Sep 1992
Abstract :
The concepts of fuzzy learning and learning in vicissitudinous environments are synergistically combined to develop a new fuzzy logic based approach to the problem of pattern recognition in variably supervised environments. The fuzziness imposed on the recognition process by the varying imperfectness in the supervision is modeled with fuzzy membership functions. The learning under the environment is simultaneously accompanied by learning about the vicissitudinous nature of the environment and the fuzzy membership functions
Keywords :
fuzzy logic; fuzzy set theory; learning (artificial intelligence); pattern recognition; fuzzy learning; fuzzy logic; fuzzy membership functions; pattern recognition; variably supervised environments; vicissitudinous environments; Fuzzy logic; Object detection; Pattern recognition; Recursive estimation; Uncertainty;
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.1992.201827
