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Fernando Palacios López
Fernando Palacios López
Unknown affiliation
Verified email at unirioja.es
Title
Cited by
Cited by
Year
Automated grapevine flower detection and quantification method based on computer vision and deep learning from on-the-go imaging using a mobile sensing platform under field …
F Palacios, G Bueno, J Salido, MP Diago, I Hernández, J Tardaguila
Computers and Electronics in Agriculture 178, 105796, 2020
652020
On‐the‐go assessment of vineyard canopy porosity, bunch and leaf exposure by image analysis
MP Diago, A Aquino, B Millan, F Palacios, J Tardáguila
Australian Journal of Grape and Wine Research 25 (3), 363-374, 2019
342019
A non-invasive method based on computer vision for grapevine cluster compactness assessment using a mobile sensing platform under field conditions
F Palacios, MP Diago, J Tardaguila
Sensors 19 (17), 3799, 2019
332019
Vineyard pruning weight assessment by machine vision: towards an on-the-go measurement system: This article is published in cooperation with the 21th GIESCO International …
B Millan, MP Diago, A Aquino, F Palacios, J Tardaguila
Oeno One 53 (2), 2019
212019
Deep learning and computer vision for assessing the number of actual berries in commercial vineyards
F Palacios, P Melo-Pinto, MP Diago, J Tardaguila
biosystems engineering 218, 175-188, 2022
192022
Impact of leaf occlusions on yield assessment by computer vision in commercial vineyards
R Íñiguez, F Palacios, I Barrio, I Hernández, S Gutiérrez, J Tardaguila
Agronomy 11 (5), 1003, 2021
152021
Early yield prediction in different grapevine varieties using computer vision and machine learning
F Palacios, MP Diago, P Melo-Pinto, J Tardaguila
Precision Agriculture 24 (2), 407-435, 2023
142023
Assessment of downy mildew in grapevine using computer vision and fuzzy logic. Development and validation of a new method
I Hernández, S Gutiérrez, S Ceballos, F Palacios, SL Toffolatti, ...
International Viticulture and Enology Society, 2022
82022
Computer vision and artificial intelligence for yield components' assessment in digital viticulture
F Palacios
Universidad de La Rioja, 2021
2021
Assessing actual number of grapevine berries using linear methods and machine learning
F Palacios, P Melo-Pinto, MP Diago, R Iñiguez, J Tardaguila
Precision agriculture’21, 4-8, 2021
2021
Use of non-invasive RGB imaging to assess the canopy status in organic viticulture
MP Diago, J Fernández-Novales, F Palacios, E Moreda, J Tardaguila
EQA–Environmental quality 30, 23-30, 2018
2018
Aplicación de las materias de Ingeniería de Computadores en la mejora de los Algoritmos Meméticos y Metaheurísticas en general
FP López, JC Padial
Enseñanza y aprendizaje de ingeniería de computadores: Revista de …, 2015
2015
IN-FIELD DOWNY MILDEW DETECTION IN GRAPEVINE USING COMPUTER VISION AND CONVOLUTIONAL NEURAL NETWORKS
I Hernández, S Gutiérrez, S Ceballos, R Iñiguez, F Palacios, ...
BOOK OF ABSTRACTS OF ALL THE POSTERS, 23, 0
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