Detail of Publication
| Text Language | Japanese |
|---|---|
| Authors | Masakazu Iwamura, Yoshio Furuya, Koichi Kise, Shinichiro Omachi, and Seiichi Uchida |
| Title | A General Theory of Supplementary Information Assignment and Analysis of Error Rates |
| Journal | Proceedings of MIRU 2008 |
| Presentation number | IS1-9 |
| Pages | pp.388-393 |
| Reviewed or not | Not reviewed |
| Month & Year | July 2008 |
| Abstract | Pattern recognition with supplementary information is a new pattern recognition framework that determines an output class by combining a feature vector extracted from the pattern and supplementary information suggesting the true class. Under the condition that supplementary information does not contain error, a theory that reduces error rates have been proposed. However, in the real world, we cannot observe any measure without error. Thus, in this paper, we discuss how to reduce error rates using the erroneous supplementary information, and confirm the effect experimentally using artificial samples following the normal distribution with a common covariance matrix. |
- Following file is available.
- Entry for BibTeX
@InCollection{Iwamura2008, author = {Masakazu Iwamura and Yoshio Furuya and Koichi Kise and Shinichiro Omachi and Seiichi Uchida}, title = {A General Theory of Supplementary Information Assignment and Analysis of Error Rates}, booktitle = {Proceedings of MIRU 2008}, year = 2008, month = jul, presenID = {IS1-9}, pages = {388--393} }