Summary
A mathematical model, which extends the Bayesian problem of pattern recognition by fusion of external context variables and patterns is proposed and investigated. Then, its empirical version is discussed and a learning algorithm for an orthogonal neural net is proposed, which takes context variables into account. The proposed algorithm has a recursive form, which is well suited for learning from a stream of patterns, which arise when features are extracted from a video sequence.
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Rafajłowicz, E. (2009). Fusion of External Context and Patterns – Learning from Video Streams. In: Kurzynski, M., Wozniak, M. (eds) Computer Recognition Systems 3. Advances in Intelligent and Soft Computing, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-93905-4_4
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DOI: https://doi.org/10.1007/978-3-540-93905-4_4
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