Using mixtures of deformable models to capture variations in hand printed
digits. Michael Revow, Christopher K. I. Williams and Geoffrey E. Hinton.
Third International workshop on Frontiers in Handwriting Recognition, Buffalo,
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Adaptive elastic models for hand-printed character recognition. Geoffrey
E. Hinton, Christopher K. I. Williams and Michael Revow. In NIPS 4, J.E.
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Other Approaches for Handwritten Digit Recognition
Modeling the Manifolds of Images of Handwritten Digits. Geoffrey
E. Hinton, Peter Dayan and Michael Revow. IEEE transactions on Neural
Networks vol 8, 65-74 1997.abstractpostscript (28 pages)
Using generative models for handwritten digit recognition. Michael Revow,
Christopher K. I. Williams and Geoffrey E. Hinton. IEEE Transactions Pattern
Analysis and Machine Intellegince 18(6), pp 592-606, 1996.
abstractpostscript (35 pages)
software implementation README
Instantiating deformable models with a neural net. Christopher
K. I. Williams, Michael Revow
and Geoffrey E. Hinton. To Appear in: Computer Vision and Image Understanding
abstractpostscript (16 pages)
Recognizing handwritten digits using mixtures of linear models. Geoffrey
E. Hinton, Michael Revow and Peter Dayan. In NIPS7, G. Tesauro, D. S.
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The wake-sleep algorithm for unsupervised Neural Networks.
Hinton, G. E., Dayan, P., Frey, B. J. and Neal, R. (1995)Science, 268,
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