C. Bishop, Neural Networks for Pattern Recognition, 1995.

C. Chatelain, L. Heutte, and T. Paquet, Segmentation-driven recognition applied to numerical field extraction from handwritten incoming mail documents. Document Analysis System, pp.564-575, 2006.
DOI : 10.1007/11669487_50

URL : https://hal.archives-ouvertes.fr/hal-00435969

L. Heutte, T. Paquet, J. Moreau, Y. Lecourtier, and C. Olivier, A structural/statistical feature based vector for handwritten character recognition, Pattern Recognition Letters, vol.19, issue.7, pp.629-641, 1998.
DOI : 10.1016/S0167-8655(98)00039-7

F. Kimura, S. Tsuruoka, Y. Miyake, and M. Shridhar, Improvements of a lexicon directed algorithm for recognition of unconstrained handwritten words, Proceedings of 2nd International Conference on Document Analysis and Recognition (ICDAR '93), pp.77-785, 1994.
DOI : 10.1109/ICDAR.1993.395791

J. Liu and P. Gader, Neural networks with enhanced outlier rejection ability for off-line handwritten word recognition, Pattern Recognition, vol.35, issue.10, pp.2061-2071, 2002.
DOI : 10.1016/S0031-3203(01)00191-1

J. Milgram, R. Sabourin, and M. Cheriet, An hybrid classification system which combines model-based and discriminative approaches, pp.155-162, 2004.

U. Pal, A. Bela¨?dbela¨?d, and C. Choisy, Water reservoir based approach for touching numeral segmentation. ICDAR, pp.892-897, 2001.
URL : https://hal.archives-ouvertes.fr/inria-00100455

J. Pitrelli and M. Perrone, Confidence-scoring postprocessing for off-line handwritten-character recognition verification, ICDAR'03, pp.278-282, 2003.

L. R. Rabiner, A tutorial on hidden markov models and selected apllications in speech recognition, Readings in Speech Recognition, pp.267-296, 1990.

A. Rakotomamonjy, Optimizing auc with support vector machine, European Conference on Artificial Intelligence Workshop on ROC Curve and AI, pp.469-478, 2004.

D. Tax and R. P. Duin, Combining One-Class Classifiers, MCS '01, pp.299-308, 2001.
DOI : 10.1007/3-540-48219-9_30