Systèmes d'inférence floue auto-évolutifs : apprentissage incrémental pour la reconnaissance de gestes manuscrits

Abdullah Almaksour 1, 2 Eric Anquetil 1
1 IntuiDoc - intuitive user interaction for document
IRISA-D6 - MEDIA ET INTERACTIONS
2 IMADOC - Interprétation et Reconnaissance d’Images et de Documents
UR1 - Université de Rennes 1, INSA Rennes - Institut National des Sciences Appliquées - Rennes, CNRS - Centre National de la Recherche Scientifique : UMR6074
Abstract : We present in this paper a new method for the design of customizable self-evolving handwriting recognition systems, which are able to adapt to writing style and needs of each writer, without require time-consuming re-learning process. The presented approach is based on first-order Takagi-Sugeno fuzzy inference system. This approach involves first an incremental clustering and adaptation of the premise part of the system, and secondly, an incremental learning of the linear consequent parameters of the system using a modified version of the Recursive Least Square method.
Complete list of metadatas

Cited literature [25 references]  Display  Hide  Download

https://hal.inria.fr/hal-00741270
Contributor : Abdullah Almousa Almaksour <>
Submitted on : Friday, October 12, 2012 - 11:29:01 AM
Last modification on : Thursday, February 7, 2019 - 5:17:33 PM
Long-term archiving on : Saturday, December 17, 2016 - 12:31:32 AM

File

Almaksour_DN.pdf
Files produced by the author(s)

Identifiers

Citation

Abdullah Almaksour, Eric Anquetil. Systèmes d'inférence floue auto-évolutifs : apprentissage incrémental pour la reconnaissance de gestes manuscrits. Revue des Sciences et Technologies de l'Information - Série Document Numérique, Lavoisier, 2011, 14 (2), pp.53-76. ⟨10.3166/dn.14.2.53-76⟩. ⟨hal-00741270⟩

Share

Metrics

Record views

498

Files downloads

935