Statistical methods for speech recognition
Statistical methods for speech recognition
On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Role of Holistic Paradigms in Handwritten Word Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Connectionist Speech Recognition: A Hybrid Approach
Connectionist Speech Recognition: A Hybrid Approach
A Full English Sentence Database for Off-Line Handwriting Recognition
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Combination of Multiple Classifiers for Handwritten Word Recognition
IWFHR '02 Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition (IWFHR'02)
Handwritten Sentence Recognition
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Recognition of Cursive Roman Handwriting - Past, Present and Future
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Offline Recognition of Unconstrained Handwritten Texts Using HMMs and Statistical Language Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Holistic cursive word recognition based on perceptual features
Pattern Recognition Letters
Efficient BP Algorithms for General Feedforward Neural Networks
IWINAC '07 Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks
A holistic classification system for check amounts based on neural networks with rejection
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
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The aim of this work is to improve the performance of off-line handwritten text recognition systems based on hidden Markov models (HMM) and hybrid Markov models with neural networks (HMM/ANN). In order to study the systems without the influence of the language model, an isolated word recognition task has been performed. The analysis of the influence of word lengths on the error rates of the recognizers has lead to combine those classifiers with another one specialized in short words. To this end, various multilayer perceptrons have been trained to classify a subset of the vocabulary in a holistic manner. Combining the classifiers by means of a variation of the Borda count voting method achieves very satisfying results.