Most of the stateoftheart systems for cursive script recognition are based on a combination of neural networks (NN) and hidden Markov models (HMMs) 1;2 . The postprocessing stage is almost exclusively modeled using HMMs and the dynamic programming (DP) technique (the Viterbi algorithm) is used to efficiently search the space of possible segmentations. In this work we introduce a neural networkbased model for representing handwritten patterns as an alternative to HMMs. In addition, we present a new algorithm that uses context information to segment, modify and organize bottom up information in order to achieve successful recognition
This paper describes an enhanced neural network-based segmentation technique for improving the segme...
International audienceHandwritten word recognition has received a substantial amount of attention in...
Comparisons are made between a number of stroke-based and character-based recognizers of connected c...
Microsoft, Motorola, Siemens, Hitachi, IAPR, NICI, IUF Most of the stateoftheart systems for curs...
Optical character recognition (OCR) software has advanced greatly in recent years. Machine-printed t...
Presents a new approach to cursive script recognition which combines syntactic pattern recognition w...
In this paper a system for on-line cursive handwriting recognition is described. The system is based...
AbstractÐIn this paper, a new analytic scheme, which uses a sequence of segmentation and recognition...
In this paper, a new analytic scheme, which uses a sequence of segmentation and recognition algorith...
This thesis investigates a method for using contextual information in text recognition. This is base...
Cursive script recognition is commonly based on finding letters within a word and recognizing them s...
Cursive handwriting is the most natural way for humans to communicate and record information. The de...
Handwritten recognition is of immense importance for processing of bank checks, postal address, form...
A tool that can search over large code corpus directly and list ranked snippets can prove to be an i...
flannGnick.cs.usu.edu This paper introduces a new recognition-based segmentation ap-proach to recogn...
This paper describes an enhanced neural network-based segmentation technique for improving the segme...
International audienceHandwritten word recognition has received a substantial amount of attention in...
Comparisons are made between a number of stroke-based and character-based recognizers of connected c...
Microsoft, Motorola, Siemens, Hitachi, IAPR, NICI, IUF Most of the stateoftheart systems for curs...
Optical character recognition (OCR) software has advanced greatly in recent years. Machine-printed t...
Presents a new approach to cursive script recognition which combines syntactic pattern recognition w...
In this paper a system for on-line cursive handwriting recognition is described. The system is based...
AbstractÐIn this paper, a new analytic scheme, which uses a sequence of segmentation and recognition...
In this paper, a new analytic scheme, which uses a sequence of segmentation and recognition algorith...
This thesis investigates a method for using contextual information in text recognition. This is base...
Cursive script recognition is commonly based on finding letters within a word and recognizing them s...
Cursive handwriting is the most natural way for humans to communicate and record information. The de...
Handwritten recognition is of immense importance for processing of bank checks, postal address, form...
A tool that can search over large code corpus directly and list ranked snippets can prove to be an i...
flannGnick.cs.usu.edu This paper introduces a new recognition-based segmentation ap-proach to recogn...
This paper describes an enhanced neural network-based segmentation technique for improving the segme...
International audienceHandwritten word recognition has received a substantial amount of attention in...
Comparisons are made between a number of stroke-based and character-based recognizers of connected c...