Abstract. A novel, fast feature selection method for hidden Markov model (HMM) based classifiers is introduced in this paper. It is also shown how this method can be used to create ensembles of classifiers. The proposed methods are tested in the context of a handwritten text recognition task
In this book, we introduce several methods for recognising unconstrained handwritten words and digit...
Research in off-line handwriting recognition has been prevalent for many decades. After many years o...
International audienceHandwritten word recognition has received a substantial amount of attention in...
In this paper we introduce a new strategy for improving a discrete HMMbased handwriting recognition...
This paper investigates the performance of hidden Markov models (HMMs) for handwriting recognition. ...
This paper investigates the performance of hidden Markov models (HMMs) for handwriting recognition. ...
This paper investigates the performance of hidden Markov models (HMMs) for handwriting recognition. ...
In this paper we introduce a new strategy for improving a discrete HMM-based handwriting recognition...
This paper investigates the performance of hidden Markov models (HMMs) for handwriting recognition. ...
Handwritten recognition is of immense importance for processing of bank checks, postal address, form...
This thesis deals with different aspects of automatic online handwriting recognition, comprising met...
Handwriting recognition is a main topic of Optical Character Recognition (OCR), which has a very wid...
Hidden Markov models are frequently used in handwriting-recognition applications. While a large numb...
Hidden Markov models are frequently used in handwriting-recognition applications. While a large numb...
Recognition rate of handwritten character is still limited around 90 percent due to the presence of ...
In this book, we introduce several methods for recognising unconstrained handwritten words and digit...
Research in off-line handwriting recognition has been prevalent for many decades. After many years o...
International audienceHandwritten word recognition has received a substantial amount of attention in...
In this paper we introduce a new strategy for improving a discrete HMMbased handwriting recognition...
This paper investigates the performance of hidden Markov models (HMMs) for handwriting recognition. ...
This paper investigates the performance of hidden Markov models (HMMs) for handwriting recognition. ...
This paper investigates the performance of hidden Markov models (HMMs) for handwriting recognition. ...
In this paper we introduce a new strategy for improving a discrete HMM-based handwriting recognition...
This paper investigates the performance of hidden Markov models (HMMs) for handwriting recognition. ...
Handwritten recognition is of immense importance for processing of bank checks, postal address, form...
This thesis deals with different aspects of automatic online handwriting recognition, comprising met...
Handwriting recognition is a main topic of Optical Character Recognition (OCR), which has a very wid...
Hidden Markov models are frequently used in handwriting-recognition applications. While a large numb...
Hidden Markov models are frequently used in handwriting-recognition applications. While a large numb...
Recognition rate of handwritten character is still limited around 90 percent due to the presence of ...
In this book, we introduce several methods for recognising unconstrained handwritten words and digit...
Research in off-line handwriting recognition has been prevalent for many decades. After many years o...
International audienceHandwritten word recognition has received a substantial amount of attention in...