154 research outputs found
Investigating the impact of combining handwritten signature and keyboard keystroke dynamics for gender prediction
© 2019 IEEE. The use of soft-biometric data as an auxiliary tool on user identification is already well known. Gender, handorientation and emotional state are some examples which can be called soft-biometrics. These soft-biometric data can be predicted directly from the biometric templates. It is very common to find researches using physiological modalities for soft-biometric prediction, but behavioural biometric is often not well explored for this context. Among the behavioural biometric modalities, keystroke dynamics and handwriting signature have been widely explored for user identification, including some soft-biometric predictions. However, in these modalities, the soft-biometric prediction is usually done in an individual way. In order to fill this space, this study aims to investigate whether the combination of those two biometric modalities can impact the performance of a soft-biometric data, gender prediction. The main aim is to assess the impact of combining data from two different biometric sources in gender prediction. Our findings indicated gains in terms of performance for gender prediction when combining these two biometric modalities, when compared to the individual ones
Influência de dados censurados no cálculo da concentração média das variáveis de qualidade da água demanda química de oxigênio e fosfato
Bagaço de mandioca em dietas de novilhas leiteiras: consumo de nutrientes e desempenho produtivo
Grão de milheto em suplementos para terminação de bovinos de corte em sistema integração lavoura e pecuária
Intake, performance and nutrient digestibility of sheep fed sugarcane treated and ensiled with calcium oxide or urea
Detection of areas of endemism on two spatial scales using Parsimony Analysis of Endemicity (PAE): the Neotropical region and the Atlantic Forest
- …