Modeling the manifolds of images of handwritten digits 论文

详细信息

发表期刊/会议

IEEE Transactions on Neural Networks

发表日期

1997-01-01

发表年份

1997

摘要

This paper describes two new methods for modeling the manifolds of digitized images of handwritten digits. The models allow a priori information about the structure of the manifolds to be combined with empirical data. Accurate modeling of the manifolds allows digits to be discriminated using the relative probability densities under the alternative models. One of the methods is grounded in principal components analysis, the other in factor analysis. Both methods are based on locally linear low-dimensional approximations to the underlying data manifold. Links with other methods that model the manifold are discussed.