Abstract
Interactive Pattern Recognition concepts and techniques are applied to problems with structured output; i.e., problems in which the result is not just a simple class label, but a suitable structure of labels. For illustration purposes (a simplification of) the problem of Human Karyotyping is considered. Results show that a) taking into account label dependencies in a karyogram significantly reduces the classical (non-interactive) chromosome label prediction error rate and b) they are further improved when interactive processing is adopted.
Work supported by the MIPRCV Spanish MICINN “Consolider Ingenio 2010” program (CSD2007-00018). Work supported by the Spanish CICyT through project TIN2009-14205-C04-01. This work was supported in part by the IST Programme of the European Community, under the PASCAL2 Network of Excellence, IST-2007-216886.
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References
Dechter, R., Pearl, J.: Generalized best-first search strategies and the optimality of A*. J. ACM 32, 505–536 (1985), http://doi.acm.org/10.1145/3828.3830
Duda, R.O., Hart, P.E.: Pattern Classification and Scene Analysis. Wiley, Chichester (1973)
Jelinek, F.: Statistical Methods for Speech Recognition. MIT Press, Cambridge (1998)
Kao, J.H., Chuang, J.H., Wang, T.: Chromosome classification based on the band profile similarity along approximate medial axis. Pattern Rec. 41, 77–89 (2008)
Martínez, C., García, H., Juan, A.: Chromosome classification using continuous hidden markov models. In: Perales, F.J., Campilho, A.C., Pérez, N., Sanfeliu, A. (eds.) IbPRIA 2003. LNCS, vol. 2652, pp. 494–501. Springer, Heidelberg (2003)
Martínez, C., Juan, A., Casacuberta, F.: Iterative contextual recurrent classification of chromosomes. Neural Processing Letters 26(3), 159–175 (2007)
Pearl, J.: Heuristics - Intelligent Search Strategies for Computer Problem Solving. Addison-Wesley, Reading (1985)
Ritter, G., Gallegos, M., Gaggermeier, K.: Automatic context-sensitive karyotyping of human chromosomes based on elliptically symmetric statistical distributions. Pattern Recognition 28(6), 823–831 (1995)
Schröck, E., du Manoir, S., Veldman, T., Schoell, B., Wienberg, J., Ferguson-Smith, M.A., Ning, Y., Ledbetter, D.H., Bar-Am, I., Soenksen, D., Garini, Y., Ried, T.: Multicolor spectral karyotyping of human chromosomes. Science 273(5274), 494–497 (1996)
Vidal, E., Castro, M.: Classification of Banded Chromosomes using Error-Correcting Grammatical Inference (ECGI) and Multilayer Perceptron (MLP). In: Sanfeliu, A., Villanueva, J., Vitriá, J. (eds.) In VII National Symposium on Pattern Recognition and Image Analysis, Barcelona, pp. 31–36 (1997)
Vidal, E., Rodríguez, L., Casacuberta, F., García-Varea, I.: Interactive pattern recognition. In: Popescu-Belis, A., Renals, S., Bourlard, H. (eds.) MLMI 2007. LNCS, vol. 4892, pp. 60–71. Springer, Heidelberg (2008)
Viterbi, A.: Error bounds for convolutional codes and an asymptotically optimal decoding algorithm. IEEE Transactions on Information Theory 13, 260–269 (1967)
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Oncina, J., Vidal, E. (2011). Interactive Structured Output Prediction: Application to Chromosome Classification. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_32
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DOI: https://doi.org/10.1007/978-3-642-21257-4_32
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