Image analysis with deep learning for early detection of downy mildew in grapevine |
I Hernández, S Gutiérrez, J Tardaguila. |
2024 |
In-field disease symptom detection and localisation using explainable deep learning: Use case for downy mildew in grapevine |
I Hernández, S Gutiérrez, I Barrio, R Íñiguez, J Tardaguila. |
2024 |
NIR attribute selection for the development of vineyard water status predictive models |
M Marañón, J Fernández-Novales, J Tardaguila, S Gutiérrez, MP Diago. |
2023 |
Multi-sensor spectral fusion to model grape composition using deep learning |
S Gutiérrez, J Fernández-Novales, T Garde-Cerdán, S Marín-San Román, .... |
2023 |
Evolutionary conditional GANs for supervised data augmentation: The case of assessing berry number per cluster in grapevine |
S Gutiérrez, J Tardaguila. |
2023 |
Perilesional edema diameter associated with brain metastases as a predictive factor of response to radiotherapy in non-small cell lung cancer |
O Arrieta, LM Bolaño-Guerra, E Caballé-Pérez, L Lara-Mejía, JG Turcott, .... |
2023 |
Inteligencia artificial y visión por ordenador para evaluar los componentes del rendimiento de la vid en viñedos comerciales |
R Íñiguez, C Poblete-Echeverría, I Hernández, S Gutiérrez, I Barrio, .... |
2023 |
Using artificial intelligence (AI) for grapevine disease detection based on images |
C Poblete-Echeverría, I Hernández, S Gutiérrez, R Iñiguez, I Barrio, .... |
2023 |
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, .... |
2022 |
ATOPE+: Supporting Personalized Exercise Interventions in Breast Cancer Care using Mobile Technologies and Machine Learning |
SM Gutiérrez, OB Legrán, MD Hermoso. |
2022 |
Deep learning for the differentiation of downy mildew and spider mite in grapevine under field conditions |
S Gutiérrez, I Hernández, S Ceballos, I Barrio, AM Díez-Navajas, .... |
2021 |
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. |
2021 |
Assessing and mapping vineyard water status using a ground mobile thermal imaging platform |
S Gutiérrez, J Fernández-Novales, MP Diago, R Iñiguez, J Tardaguila. |
2021 |
Smart applications and digital technologies in viticulture: A review |
J Tardaguila, M Stoll, S Gutiérrez, T Proffitt, MP Diago. |
2021 |
Artificial Intelligence and Novel Sensing Technologies for Assessing Downy Mildew in Grapevine |
I Hernández, S Gutiérrez, S Ceballos, R Iñíguez, I Barrio, J Tardaguila. |
2021 |
Impact of Leaf Occlusions on Yield Assessment by Computer Vision in Commercial Vineyards. Agronomy 2021, 11, 1003 |
R Íñiguez, F Palacios, I Barrio, I Hernández, S Gutiérrez, J Tardaguila. |
2021 |
Prospects of thermal imaging as a non-invasive tool to assess water status for irrigation scheduling in commercial vineyards |
J Tardáguila, MP Diago, J Fernández-Novales, I Hernández, S Gutiérrez, .... |
2020 |
Ground based hyperspectral imaging for extensive mango yield estimation |
S Gutiérrez, A Wendel, J Underwood. |
2019 |
On‐the‐go hyperspectral imaging for the in‐field estimation of grape berry soluble solids and anthocyanin concentration |
S Gutiérrez, J Tardáguila, J Fernández‐Novales, MP Diago. |
2019 |
Spectral filter design based on in-field hyperspectral imaging and machine learning for mango ripeness estimation |
S Gutiérrez, A Wendel, J Underwood. |
2019 |
On-The-Go VIS+ SW− NIR spectroscopy as a reliable monitoring tool for grape composition within the vineyard |
J Fernández-Novales, J Tardáguila, S Gutiérrez, MP Diago. |
2019 |
Hyperspectral imaging application under field conditions: assessment of the spatio-temporal variability of grape composition within a vineyard |
S Gutierrez, MP Diago, J Fernandez-Novales, J Tardaguila. |
2019 |
Vineyard water status assessment using on-the-go thermal imaging and machine learning |
S Gutiérrez, MP Diago, J Fernández-Novales, J Tardaguila. |
2018 |
On-the-go hyperspectral imaging under field conditions and machine learning for the classification of grapevine varieties |
S Gutiérrez, J Fernández-Novales, MP Diago, J Tardaguila. |
2018 |
Development and validation of a new methodology to assess the vineyard water status by on-the-go near infrared spectroscopy |
MP Diago, J Fernández-Novales, S Gutiérrez, M Marañón, J Tardaguila. |
2018 |
In field quantification and discrimination of different vineyard water regimes by on-the-go NIR spectroscopy |
J Fernández-Novales, J Tardaguila, S Gutiérrez, M Marañón, MP Diago. |
2018 |
Physical requirements for vineyard monitoring robots |
V Saiz-Rubio, M Diago, F Rovira-Más, A Cuenca, S Gutiérrez, .... |
2018 |
Non‐destructive assessment of grapevine water status in the field using a portable NIR spectrophotometer |
J Tardaguila, J Fernández‐Novales, S Gutiérrez, MP Diago. |
2017 |
On-the-go thermal imaging for water status assessment in commercial vineyards |
S Gutiérrez, MP Diago, J Fernández-Novales, J Tardaguila. |
2017 |
Vineyard water status assessment by non-destructive, proximal, NIR spectroscopy |
J Fernández-Novales, S Gutiérrez, A Gonzalo-Diago. |
2017 |
Landmark-based music recognition system optimisation using genetic algorithms |
S Gutiérrez, S García. |
2016 |
Data mining and NIR spectroscopy in viticulture: applications for plant phenotyping under field conditions |
S Gutiérrez, J Tardaguila, J Fernández-Novales, MP Diago. |
2016 |
Near infrared spectroscopy and data mining: classification of grapevine varieties |
S Gutiérrez, J Tardáguila, J Fernández-Novales, MP Diago. |
2016 |
Vineyard water status estimation with near infrared spectroscopy and data mining |
S Gutiérrez, J Tardáguila, J Fernández-Novales, MP Diago. |
2016 |
A new app for smartphones to count the number of flowers per inflorescence under field conditions |
MP Diago, A Aquino, S Gutiérrez, D Gastón, B Millán Prior. |
2016 |
NIR attribute selection for vineyard water status modelling |
M Marañón Grandes, J Fernández-Novales, S Gutiérrez, J Tardáguila, .... |
2016 |
Boolean Model for Grapevine Yield Estimation on 2D Images Taken Under Field conditions |
B Millán Prior, A Aquino, MP Diago, J Fernández-Novales, S Gutiérrez, .... |
2016 |
Grape Segmentation in Vine Images Automatically Taken with a Modified Ground |
A Aquino, B Millán Prior, MP Diago, J Fernández-Novales, S Gutiérrez, .... |
2016 |
Uso de la espectroscopía NIR como herramienta de monitorización no invasiva del estado hídrico del viñedo |
MP Diago, J Fernández-Novales, S Gutiérrez, M Marañón Grandes, .... |
2016 |
Assessing Grapevine Canopy Gaps from On-The-Go Image Vision |
MP Diago, A Aquino, B Millán Prior, I Barrio Fernández, .... |
2016 |
Vineyard Water Monitoring Using Models Based on Thermal Imaging |
S Gutiérrez, J Fernández-Novales, B Millán Prior, A Aquino, J Tardáguila, .... |
2016 |
Developing NIR models for the on-the-go estimation of vineyard water status |
J Fernández-Novales, M Marañón Grandes, S Gutiérrez, J Tardáguila, .... |
2016 |
Support vector machine and artificial neural network models for the classification of grapevine varieties using a portable NIR spectrophotometer |
S Gutiérrez, J Tardaguila, J Fernández-Novales, MP Diago. |
2015 |
Grapevine flower estimation by applying artificial vision techniques on images with uncontrolled scene and multi-model analysis |
A Aquino, B Millan, S Gutiérrez, J Tardáguila. |
2015 |
Data mining and non-invasive proximal sensing for precision viticulture |
S Gutiérrez, J Tardaguila, J Fernández-Novales, MP Diago. |
2015 |
In-field assessment of grapevine water status using a portable NIR spectrophotometer |
J Fernández-Novales, S Gutiérrez, J Tardáguila, B Millan, MP Diago. |
2015 |
Original data from manuscript entitled: Support Vector Machine and Artificial Neural Network Models for the Classification of Grapevine Varieties Using a Portable NIR … |
S Gutiérrez, J Tardáguila, J Fernández-Novales, MP Diago. |
2015 |
Optical flow and scale-space theory applied to seaice motion estimation |
S Gutiérrez, DG Long. |
2003 |