DocumentCode
2054955
Title
Towards an information theoretic framework for object recognition
Author
Westover, M. Brandon ; O´Sullivan, Joseph A.
Author_Institution
Dept. of Phys., Washington Univ., St. Louis, MO, USA
fYear
2004
fDate
27 June-2 July 2004
Firstpage
219
Abstract
We propose a model for rate-constrained pattern recognition problems, and present single-letter information bounds governing the conditions under which asymptotically error-free recognition is possible. The bounds depend on the statistics of the training and testing data, the number of pattern classes, and the rates of the codes used by the recognition system to internalize the data.
Keywords
encoding; object recognition; problem solving; asymptotic error-free recognition; code rate; data testing; information theory; object recognition; pattern class; pattern testing; pattern training; rate-constrained pattern recognition; Electronic mail; Force sensors; Object recognition; Pattern recognition; Physics; Sensor systems; Statistical analysis; System testing; Systems engineering and theory; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2004. ISIT 2004. Proceedings. International Symposium on
Print_ISBN
0-7803-8280-3
Type
conf
DOI
10.1109/ISIT.2004.1365256
Filename
1365256
Link To Document