An evaluation of ensemble methods in handwritten word recognition based on feature selection
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[1] Horst Bunke,et al. Using a Statistical Language Model to Improve the Performance of an HMM-Based Cursive Handwriting Recognition System , 2001, Int. J. Pattern Recognit. Artif. Intell..
[2] Robert P. W. Duin,et al. Experiments with Classifier Combining Rules , 2000, Multiple Classifier Systems.
[3] Horst Bunke,et al. Fast Feature Selection in an HMM-Based Multiple Classifier System for Handwriting Recognition , 2003, DAGM-Symposium.
[4] Thomas G. Dietterich. Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.
[5] Gyeonghwan Kim,et al. An architecture for handwritten text recognition systems , 1999, International Journal on Document Analysis and Recognition.
[6] Horst Bunke,et al. Hidden Markov model length optimization for handwriting recognition systems , 2002, Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition.
[7] Josef Kittler,et al. Floating search methods in feature selection , 1994, Pattern Recognit. Lett..
[8] Horst Bunke,et al. Optimizing the number of states, training iterations and Gaussians in an HMM-based handwritten word recognizer , 2003, Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings..
[9] J.-C. Simon,et al. Off-line cursive word recognition , 1992, Proc. IEEE.
[10] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[11] Horst Bunke,et al. The IAM-database: an English sentence database for offline handwriting recognition , 2002, International Journal on Document Analysis and Recognition.
[12] Torsten Caesar,et al. Sophisticated topology of hidden Markov models for cursive script recognition , 1993, Proceedings of 2nd International Conference on Document Analysis and Recognition (ICDAR '93).
[13] Lawrence R. Rabiner,et al. A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.
[14] Adam Krzyżak,et al. Methods of combining multiple classifiers and their applications to handwriting recognition , 1992, IEEE Trans. Syst. Man Cybern..
[15] Lee Luan Ling,et al. Disconnected handwritten numeral image recognition , 1997, Proceedings of the Fourth International Conference on Document Analysis and Recognition.
[16] Ching Y. Suen,et al. Computer recognition of unconstrained handwritten numerals , 1992, Proc. IEEE.
[17] Horst Bunke,et al. Automatic bankcheck processing , 1997 .
[18] Kagan Tumer,et al. Input Decimation Ensembles: Decorrelation through Dimensionality Reduction , 2001, Multiple Classifier Systems.
[19] K. Maruyama,et al. RECOGNITION METHOD FOR CURSIVE JAPANESE WORD WRITTEN IN LATIN CHARACTERS , 2004 .
[20] Tin Kam Ho,et al. The Random Subspace Method for Constructing Decision Forests , 1998, IEEE Trans. Pattern Anal. Mach. Intell..
[21] Ching Y. Suen,et al. Multiple Classifier Combination Methodologies for Different Output Levels , 2000, Multiple Classifier Systems.
[22] William B. Yates,et al. Engineering Multiversion Neural-Net Systems , 1996, Neural Computation.
[23] Horst Bunke,et al. Creation of classifier ensembles for handwritten word recognition using feature selection algorithms , 2002, Proceedings Eighth International Workshop on Frontiers in Handwriting Recognition.
[24] Simon Günter,et al. Multiple classifier systems in offline cursive handwriting recognition , 2004 .