The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Modeling the manifolds of images of handwritten digits
Abstract
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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Citations
Cites
Statistical Methods for Rates and Proportions
Fleiss, J. L., Levin, B., & Paik, M. C. (2003) · Wiley Series in Probability and Statistics · doi:10.1002/0471445428 · Cited by 18,646
The Representation and Matching of Pictorial Structures
Fischler, M. A., & Elschlager, R. A. (1973) · IEEE Transactions on Computers · doi:10.1109/t-c.1973.223602 · Cited by 1,322
Cited by
McLachlan, G., & Peel, D. (2000) · Wiley Series in Probability and Statistics · doi:10.1002/0471721182 · Cited by 10,991
Detecting faces in images: a survey
Yang, M.-H., Kriegman, D. J., & Ahuja, N. (2002) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.982883 · Cited by 3,427
Dayan, P., Hinton, G. E., Neal, R. M., & Zemel, R. S. (1995) · Neural Computation · doi:10.1162/neco.1995.7.5.889 · Cited by 1,207
Self-citationIncremental nonlinear dimensionality reduction by manifold learning
Law, M. H. C., & Jain, A. K. (2006) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2006.56 · Cited by 284
Metadata
- Authors
- Hinton, G. E., Dayan, P., & Revow, M.
- Venue
- IEEE Transactions on Neural Networks
- Published
- 1997-01
- Volume
- 8
- Issue
- 1
- Pages
- 65-74
- ISSN
- 1045-9227 (ISSN-L)
- 1941-0093
- OpenAlex
- W2111842831
- Cited by
- 330
- References
- 2
- FWCI
- 19.90
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
