Modeling The Manifolds of Images of Handwritten Digits  

Oleh:

Revow, M. ; Dayan, P. ; Hinton, G. E.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 8 no. 1 (1997), page 65-74.
Topik: IMAGE; modeling; manifolds; images; handwritten; digits

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

Lihat Detail Induk

Isi artikel

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.

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