A Database for Learning Numbers by Visual Finger Recognition in Developmental Neuro-Robotics

DAVIES, Sergio, LUCAS, Alexandr, RICOLFE-VIALA, Carlos and DI NUOVO, Alessandro (2021). A Database for Learning Numbers by Visual Finger Recognition in Developmental Neuro-Robotics. Frontiers in Neurorobotics, 15.

[img]
Preview
PDF
fnbot-15-619504.pdf - Published Version
Creative Commons Attribution.

Download (2MB) | Preview
Open Access URL: https://www.frontiersin.org/articles/10.3389/fnbot... (Published version)
Link to published version:: https://doi.org/10.3389/fnbot.2021.619504
Related URLs:

    Abstract

    Numerical cognition is a fundamental component of human intelligence that has not been fully understood yet. Indeed, it is a subject of research in many disciplines, e.g., neuroscience, education, cognitive and developmental psychology, philosophy of mathematics, linguistics. In Artificial Intelligence, aspects of numerical cognition have been modelled through neural networks to replicate and analytically study children behaviours. However, artificial models need to incorporate realistic sensory-motor information from the body to fully mimic the children's learning behaviours, e.g., the use of fingers to learn and manipulate numbers. To this end, this article presents a database of images, focused on number representation with fingers using both human and robot hands, which can constitute the base for building new realistic models of numerical cognition in humanoid robots, enabling a grounded learning approach in developmental autonomous agents. The article provides a benchmark analysis of the datasets in the database that are used to train, validate, and test five state-of-the art deep neural networks, which are compared for classification accuracy together with an analysis of the computational requirements of each network. The discussion highlights the trade-off between speed and precision in the detection, which is required for realistic applications in robotics.

    Item Type: Article
    Uncontrolled Keywords: 0801 Artificial Intelligence and Image Processing; 0903 Biomedical Engineering; 1109 Neurosciences
    Identification Number: https://doi.org/10.3389/fnbot.2021.619504
    SWORD Depositor: Symplectic Elements
    Depositing User: Symplectic Elements
    Date Deposited: 09 Mar 2021 16:22
    Last Modified: 17 Mar 2021 13:16
    URI: http://shura.shu.ac.uk/id/eprint/28356

    Actions (login required)

    View Item View Item

    Downloads

    Downloads per month over past year

    View more statistics