Javier Cano, Juan-Carlos Perez-Cortes, Joaquim Arlandis, Rafael Llobet  Home/Search
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Abstract: In this paper, a process of expansion of the training set by synthetic generation of handwritten uppercase letters via deformations of natural images is tested in combination with an approximate k Nearest Neighbor (k NN) classifier. It has been previously shown [11] [10] that approximate nearest neighbors search in large databases can be successfully used in an OCR task, and that significant performance improvements can be consistently obtained by simply increasing the size of the training set. ... (Update)
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BibTeX entry: (Update)
J. Cano, J. C. Perez-Cortes, J. Arlandis, and R. Llobet. Training set expansion in handwritten character recognition. In Proc. SSPR/SPR 2002. http://citeseer.ist.psu.edu/cano02training.html More
@misc{ cano02training,
author = "J. Cano and J. Perez-Cortes and J. Arlandis and R. Llobet",
title = "Training set expansion in handwritten character recognition",
text = "J. Cano, J. C. Perez-Cortes, J. Arlandis, and R. Llobet. Training set expansion
in handwritten character recognition. In Proc. SSPR/SPR 2002.",
year = "2002",
url = "citeseer.ist.psu.edu/cano02training.html" }
Citations (may not include all citations):266 An optimal algorithm for approximate nearest neighbor search.. - Arya, Mount et al. - 1998
69 Optimal expected time algorithms for closest point problems (context) - Bentley, Weide et al. - 1980
69 The condensed nearest neighbor rule (context) - Hart
22 handwritten numeral recognition by perturbation method (context) - Ha, Bunke et al. - 1997
19 An algorithm nding best matches in logarithmic expected time (context) - Friedman, Bentley et al. - 1977
4 the edited nearest neighbour rule (context) - Devijver, Kittler - 1980
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