Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Juan Camilo Rivera-Palacio"'
Autor:
Raúl Andrés Molina-Benavides, Sandra Milena Perilla-Duque, Rómulo Campos-Gaona, Hugo Sánchez-Guerrero, Juan Camilo Rivera-Palacio, Luis Armando Muñoz-Borja, Daniel Ricardo Jiménez-Rodas
Publikováno v:
Revista MVZ Cordoba, Vol 28, Iss 3 (2023)
Objective. The main idea of this study was to quantify the relationship between climatic variables and tympanic body temperature recorded through the use of wireless sensors in grazing cows located in low tropic. Material and methods. The tympanic te
Externí odkaz:
https://doaj.org/article/f6624901cb414d6986abf6d18123bc68
Autor:
Masahiro Ryo, Josepha Schiller, Stefan Stiller, Juan Camilo Rivera Palacio, Konlavach Mengsuwan, Anastasiia Safonova, Yuqi Wei
Publikováno v:
Journal of Sustainable Agriculture and Environment. 2:40-44
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e12766782f6b5e5bc65c6d954c8c43b9
https://doi.org/10.1002/sae2.12036
https://doi.org/10.1002/sae2.12036
Autor:
Juan Camilo Rivera Palacio, Christian Bunn, Eric Rahn, Daisy Little-Savage, Paul Günter Schmidt, Masahiro Ryo
Publikováno v:
Plant Phenomics, Vol 6 (2024)
Deep learning and computer vision, using remote sensing and drones, are 2 promising nondestructive methods for plant monitoring and phenotyping. However, their applications are infeasible for many crop systems under tree canopies, such as coffee crop
Externí odkaz:
https://doaj.org/article/2ca9e6b18c5e4bed887c7061ccdf78cc
Autor:
Masahiro Ryo, Josepha Schiller, Stefan Stiller, Juan Camilo Rivera Palacio, Konlavach Mengsuwan, Anastasiia Safonova, Yuqi Wei
Publikováno v:
Journal of Sustainable Agriculture and Environment, Vol 2, Iss 1, Pp 40-44 (2023)
Abstract Deep learning is an emerging data analytic tool that can improve predictability, efficiency and sustainability in agriculture. With a bibliometric analysis of 156 articles, we show how deep learning methods have been applied in the context o
Externí odkaz:
https://doaj.org/article/899cc1d3f65d4bfe85c5f2b9216ddd19