Spotting handwritten words and REGEX using a two stage BLSTM-HMM architecture
| Autor: | Thierry Paquet, Clément Chatelain, Luc Mioulet, Gautier Bideault |
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| Přispěvatelé: | Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS), Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Institut National des Sciences Appliquées (INSA)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Université Le Havre Normandie (ULH), Normandie Université (NU), Equipe Apprentissage (DocApp - LITIS), Normandie Université (NU)-Institut national des sciences appliquées Rouen Normandie (INSA Rouen Normandie), Chatelain, Clément |
| Rok vydání: | 2015 |
| Předmět: |
Artificial neural network
Regular Expression Spotting Computer science business.industry Speech recognition [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing Pattern recognition Spotting REGEX BLSTM [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing Handwriting recognition Artificial intelligence Line (text file) Handwritten Document Hidden Markov model business Word Spotting Handwriting Recognition |
| Zdroj: | DRR Document Recognition and retrieval Document Recognition and retrieval, 2015, San Francisco, United States Document Recognition and Retrieval Document Recognition and Retrieval, 2015, San Fransisco, United States |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.2075796 |
| Popis: | International audience; In this article, we propose a hybrid model for spotting words and regular expressions (REGEX) in handwritten documents. The model is made of the state-of-the-art BLSTM (Bidirectional Long Short Time Memory) neural network for recognizing and segmenting characters, coupled with a HMM to build line models able to spot the desired sequences. Experiments on the Rimes database show very promising results. |
| Databáze: | OpenAIRE |
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