TY  - CONF
AU  - Asma Bensalah
AU  - Antonio Parziale
AU  - Giuseppe De Gregorio
AU  - Angelo Marcelli
AU  - Alicia Fornes
AU  - Josep Llados
A2  - IGS
PY  - 2023//
TI  - I Can’t Believe It’s Not Better: In-air Movement for Alzheimer Handwriting Synthetic Generation
BT  - 21st International Graphonomics Conference
SP  - 136–148
N2  - During recent years, there here has been a boom in terms of deep learning use for handwriting analysis and recognition. One main application for handwriting analysis is early detection and diagnosis in the health field. Unfortunately, most real case problems still suffer a scarcity of data, which makes difficult the use of deep learning-based models. To alleviate this problem, some works resort to synthetic data generation. Lately, more works are directed towards guided data synthetic generation, a generation that uses the domain and data knowledge to generate realistic data that can be useful to train deep learning models. In this work, we combine the domain knowledge about the Alzheimer’s disease for handwriting and use it for a more guided data generation. Concretely, we have explored the use of in-air movements for synthetic data generation.
UR  - https://link.springer.com/chapter/10.1007/978-3-031-45461-5_10
UR  - http://dx.doi.org/10.1007/978-3-031-45461-5_10
N1  - DAG
ID  - Asma Bensalah2023
ER  -