1992 Papers
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Xun Li and David G. Lowe,
Model-guided grouping for 3-D motion tracking. Proceedings of Vision Interface 92, pp. 125-130, Vancouver, B.C. May 1992.
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James J. Little, Accurate Early Detection of Discontinuities (Vision
Interface 92)
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David G. Lowe,
Robust model-based motion tracking through the integration of search and estimation. International Journal of Computer Vision, pp. 113-122. 8, 2 (August 1992).
[ps]
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David G. Lowe, Solving for 3-D model parameters from the locations of
image features. in The Robotics Review, eds. Khatib et
al. (MIT Press), pp.137-143. 1992.
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Alan K. Mackworth,
On Seeing Robots. Vision Interface, 1992.
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D. Poole,
Efficient Model-based Diagnosis: Searching in Bayesian Networks. Proceedings of the Third International Workshop on Principles of Diagnosis, Rosario, Washington, October 1992.
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D. Poole,
Logic Programming, Abduction and Probability. Proceedings of the International Conference on Fifth Generation Computer Systems, (FGCS'92), pages 530-538, Tokyo, June 1992.
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D. Poole,
Decision-theoretic Defaults. Proceedings of the Ninth Biennial Canadian Artificial Intelligence Conference, (CSCSI-92), pages 190-197, Vancouver, May 1992.
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R. Qi and D. Poole,
Two Algorithms for Decision Tree Search. Proceedings of the Second Pacific Rim International Conference on Artificial Intelligence, Seoul, Korea, pages 121-127, September 1992.
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R. Qi and D. Poole,
A Framework for U-graph Based Path Planning. Proceedings of the Second Pacific Rim International Conference on Artificial Intelligence, Seoul, Korea, pages 287-293, September 1992.
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Y. Xiang, D. Poole and M. P. Beddoes,
Exploring Locality in Bayesian Networks for Large Expert Systems. Proceedings of the Eighth Conference on Uncertainty in AI, pages 344-351, Stanford, July 1992.
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L. Zhang and D. Poole,
Stepwise-Decomposable Influence Diagrams. Proceedings of the Third International Conference on the Principles of Knowledge Representation and Reasoning, Cambridge, Mass., pages 141-152, October 1992.
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L. Zhang and D. Poole,
Sidestepping the Triangulation Problem in Bayesian Net Computation. Proceedings of the Eighth Conference on Uncertainty in AI, pages 360-367, Stanford, July 1992.
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