Výsledky vyhledávání
- 1.0560331 - ÚFM 2023 RIV NL eng C - Konferenční příspěvek (zahraniční konf.)
Pineda, Maria F. - Tinoco Navaro, Hector Andres - Lopez-Guzman, J. - Perdomo-Hurtado, L. - Cardona, Carlos I. - Rincon-Jimenez, A. - Betancur-Herrera, N.
Ripening stage classification of Coffea arabica L. var. Castillo using a Machine learning approach with the electromechanical impedance measurements of a contact device.
MATERIALS TODAY-PROCEEDINGS. Vol. 62. Amsterdam: Elsevier, 2022, s. 6671-6678. ISSN 2214-7853.
[IC4M - International Conference on Advances in Materials, Mechanics, Mechatronics and Manufacturing. Indie (IN), 09.04.2022-10.04.2022]
Institucionální podpora: RVO:68081723
Klíčová slova: Coffee fruits * coffee arabica L. var. Castillo * Electromechanical impedance * Non-destructive testing * Machine learning * Selective harvesting
Obor OECD: Materials engineering
Trvalý link: https://hdl.handle.net/11104/0333290