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Communication Dans Un Congrès Année : 2020

Gender Identification through Handwriting: an Online Approach

Résumé

The present study was designed to identify writer's gender trough online handwriting and drawing analysis. Two groups - one of 126 males (mean age 24.65, SD=2.45) and the other of 114 females (mean age 24.51, SD=2.50) participants were recruited in the experiment. They were asked to perform seven writing and drawing tasks utilizing a digitizing tablet and a special writing device. Seventeen writing features grouped into five categories have been considered. The experiment's results show that the set of considered features enable to discriminate between male and female writers investigating their performance while copying a house drawing (task 2), writing words in capital letters (task 3) and writing a complete sentence in cursive letters (task 7), in particular focusing on Ductus (number of strokes) and Time categories of writing features
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Dates et versions

hal-04277560 , version 1 (09-11-2023)

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Citer

Gennaro Cordasco, Michele Buonanno, Marcos Faundez-Zanuy, Maria Teresa Riviello, Laurence Likforman-Sulem, et al.. Gender Identification through Handwriting: an Online Approach. 2020 11th IEEE International Conference on Cognitive Infocommunications (CogInfoCom), Sep 2020, Mariehamn, Finland. pp.000197-000202, ⟨10.1109/CogInfoCom50765.2020.9237863⟩. ⟨hal-04277560⟩
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