The operation of a machine in the “physical” environment is typically supported by arithmetic models. However, when a human is involved there might emerge non-numerical data…
Our orientation is toward the development of machines with a capacity to interact with humans in various applications including education, precision farming, patrolling in the physical environment and other.
Our orientation is toward the conversion of our laboratory prototypes in commercial products.
Lytridis, C.; Kaburlasos, V.G.; Bazinas, C.; Papakostas, G.A.; Sidiropoulos, G.; Nikopoulou, V.-A.; Holeva, V.; Papadopoulou, M.; Evangeliou, A. Behavioral Data Analysis of Robot-Assisted Autism Spectrum Disorder (ASD) Interventions Based on Lattice Computing Techniques. Sensors 2022, 22, 621. https://doi.org/10.3390/s22020621
Kaburlasos, V.G. Lattice Computing: A Mathematical Modelling Paradigm for Cyber-Physical System Applications. Mathematics 2022, 10, 271. https://doi.org/10.3390/math10020271
AIRC hosted International Workshop: Trustworthy AI for the Future of Risk Management (TAI-RM2022) on 14th June, 2022, Belfast , UK. Paper deadline: 1st March 2022, Funded PhD Opportunity: Knowledged Enhanced Imbalanced Learning (KEIL). Deadline: 7th February, 2022.
AIRC hosted International Workshop: Trustworthy AI for the Future of Risk Management (TAI-RM2022) on 14th June, 2022, Belfast , UK. Paper deadline: 1st March 2022, Funded PhD Opportunity: Knowledged Enhanced Imbalanced Learning (KEIL). Deadline: 7th February, 2022.
V. G. Kaburlasos, C. Lytridis, E. Vrochidou, C. Bazinas, G. A. Papakostas, A. Lekova, O. Bouattane, M. Youssfi, T. Hashimoto, “Granule-based-classifier (GbC): a lattice computing scheme applied on tree data structures”, Mathematics, vol. 9, no. 22, 2889, 2021. https://www.mdpi.com/2227-7390/9/22/2889 (Special Issue on Lattice Computing: A Mathematical Modelling Paradigm for Cyber–Physical System Applications – Section “Computational and Applied Mathematics”. Guest Editor: Vassilis G. Kaburlasos)
E. Vrochidou, C. Bazinas, G. A. Papakostas, T. Pachidis, V. G. Kaburlasos, “A review of the state-of-art, limitations and perspectives of machine vision for grape ripening estimation”, 13th EFITA (European Federation for Information Technology in Agriculture, Food and Environment) International Conference, 25-26 May 2021. In: MDPI Engineering Proceedings 2021, 9 (1), 2; https://www.mdpi.com/2673-4591/9/1/2
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