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Self-supervised adaptation for on-line script text recognition
Outdot, Loïc (Universit Pierre et Marie Curie)
Prevost, Lionel (Universit Pierre et Marie Curie)
Milgram, Maurice

Data: 2005
Resum: We have recently developed in our lab a text recognizer for on-line texts written on a touch-terminal. We present in this paper several strategies to adapt this recognizer in a self-supervised way to a given writer and compare them to the supervised adaptation scheme. The baseline system is based on the activation-verification cognitive model. We have designed this recognizer to be writer-independent but it may be adapted to be writer-dependent in order to increase the recognition speed and rate. The classification expert can be iteratively modified in order to learn the particularities of a writer. The best self-supervised adaptation strategy is called prototype dynamic management and gets good results, close to those of the supervised methods. The combination of supervised and self-supervised strategies increases accuracy again. Results, presented on a large database of 90 texts (5,400 words) written by 38 different writers are very encouraging with an error rate lower than 10%.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. Creative Commons
Llengua: Anglès.
Document: article ; recerca ; publishedVersion
Matèria: Handwriting recognition ; Supervised adaptation ; Self-supervised adaptation ; Model-based classifier ; Reconeixement manuscrit ; Adaptació supervisada ; Adaptació autosupervisada ; Reconocimiento manuscrito ; Adaptación supervisada ; Adaptación autosupervisada
Publicat a: ELCVIA : Electronic Letters on Computer Vision and Image Analysis, V. 5 n. 2 (2005) p. 87-97, ISSN 1577-5097

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