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Online learning the consensus of multiple correspondences between sets. (2015)
Journal Article
MORENO-GARCÍA, C.F. and SERRATOSA, F. 2015. Online learning the consensus of multiple correspondences between sets. Knowledge-based systems [online], 90, pages 49-57. Available from: https://doi.org/10.1016/j.knosys.2015.09.034

When several subjects solve the assignment problem of two sets, differences on the correspondences computed by these subjects may occur. These differences appear due to several factors. For example, one of the subjects may give more importance to som... Read More about Online learning the consensus of multiple correspondences between sets..

Correspondence consensus of two sets of correspondences through optimisation functions. (2015)
Journal Article
MORENO-GARCÍA, C.F. and SERRATOSA, F. 2017. Correspondence consensus of two sets of correspondences through optimisation functions. Pattern analysis and applications [online], 20(1), pages 201-213. Available from: https://doi.org/10.1007/s10044-015-0486-y

We present a consensus method which, given the two correspondences between sets of elements generated by separate entities, enounces a final correspondence consensus considering the existence of outliers. Our method is based on an optimisation techni... Read More about Correspondence consensus of two sets of correspondences through optimisation functions..

An interactive model for structural pattern recognition based on the Bayes classifier. (2015)
Conference Proceeding
CORTÉS, X., SERRATOSA, F. and MORENO-GARCÍA, C.F. 2015. An interactive model for structural pattern recognition based on the Bayes classifier. In De Marsico, M., Figueiredo, M. and Fred, A. (eds.) Proceedings of 4th International conference on pattern recognition applications and methods (ICPRAM 2015), 10-12 January 2015, Lisbon, Portugal, vol 1. Setubal: SCITEPRSS [online], pages 240-247. Available from: https://doi.org/10.5220/0005201602400247

This paper presents an interactive model for structural pattern recognition based on a naïve Bayes classifier. In some applications, the automatically computed correlation between local parts of two images is not good enough. Moreover, humans are ver... Read More about An interactive model for structural pattern recognition based on the Bayes classifier..