Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Arantza Bereciartua-Perez"'
Autor:
Artzai Picon, Arantza Bereciartua-Perez, Itziar Eguskiza, Javier Romero-Rodriguez, Carlos Javier Jimenez-Ruiz, Till Eggers, Christian Klukas, Ramon Navarra-Mestre
Publikováno v:
Artificial Intelligence in Agriculture, Vol 6, Iss , Pp 199-210 (2022)
Performing accurate and automated semantic segmentation of vegetation is a first algorithmic step towards more complex models that can extract accurate biological information on crop health, weed presence and phenological state, among others. Traditi
Externí odkaz:
https://doaj.org/article/24f8f33bb0b2469f93bb1c8982ce1044
Autor:
Itziar Egusquiza, Artzai Picon, Unai Irusta, Arantza Bereciartua-Perez, Till Eggers, Christian Klukas, Elisabete Aramendi, Ramon Navarra-Mestre
Publikováno v:
Frontiers in Plant Science, Vol 13 (2022)
Plant fungal diseases are one of the most important causes of crop yield losses. Therefore, plant disease identification algorithms have been seen as a useful tool to detect them at early stages to mitigate their effects. Although deep-learning based
Externí odkaz:
https://doaj.org/article/47227d6cff2c4893a9be2ac32791bfc9
Autor:
Arantza Bereciartua-Perez, Gorka Duro, Jone Echazarra, Francico Javier González, Alberto Serrano, Liher Irizar
Publikováno v:
Applied Sciences, Vol 12, Iss 21, p 11192 (2022)
Glass bottle-manufacturing companies produce bottles of different colors, shapes and sizes. One identified problem is that seeds appear in the bottle mainly due to the temperature and parameters of the oven. This paper presents a new system capable o
Externí odkaz:
https://doaj.org/article/14ae041077f249b5abcaac72566d3378
Autor:
Arantza Bereciartua-Pérez, María Monzón, Daniel Múgica, Greta De Both, Jeroen Baert, Brittany Hedges, Nicole Fox, Jone Echazarra, Ramón Navarra-Mestre
Publikováno v:
Artificial Intelligence in Agriculture, Vol 13, Iss , Pp 18-31 (2024)
Estimation of damage in plants is a key issue for crop protection. Currently, experts in the field manually assess the plots. This is a time-consuming task that can be automated thanks to the latest technology in computer vision (CV). The use of imag
Externí odkaz:
https://doaj.org/article/4ebf665d342643e98dcdff5727dbd928
Autor:
Laura Gómez-Zamanillo, Pablo Galán, Arantza Bereciartúa-Pérez, Artzai Picón, José Miguel Moreno, Markus Berns, Jone Echazarra
Publikováno v:
Smart Agricultural Technology, Vol 9, Iss , Pp 100555- (2024)
Vegetable breeding companies invest a considerable amount of their resources in phenotyping. The advancement of computer vision technology has made it possible to digitalize these processes, leading to improved efficiency and quality. However, phenot
Externí odkaz:
https://doaj.org/article/a646ecded6db4320a6393ac87d34c3c7
Autor:
Laura Gómez-Zamanillo, Arantza Bereciartua-Pérez, Artzai Picón, Liliana Parra, Marian Oldenbuerger, Ramón Navarra-Mestre, Christian Klukas, Till Eggers, Jone Echazarra
Publikováno v:
Smart Agricultural Technology, Vol 5, Iss , Pp 100243- (2023)
Greenhouse plant assessment is key part in the process of developing and testing new herbicides as it serves to analyze the response of the species to those different products and doses in a controlled way. With that purpose, trials are carried out i
Externí odkaz:
https://doaj.org/article/326a636fbc49414789b6a28b912cdad8
Autor:
Arantza Bereciartua-Pérez, Laura Gómez, Artzai Picón, Ramón Navarra-Mestre, Christian Klukas, Till Eggers
Publikováno v:
Smart Agricultural Technology, Vol 3, Iss , Pp 100125- (2023)
The use of digital technologies and artificial intelligence techniques for the automation of some visual assessment processes in agriculture is currently a reality. Image-based, and recently deep learning-based systems are being used in several appli
Externí odkaz:
https://doaj.org/article/de3f01d16d4d4ef39c4f3f9b1bd74a72