Publicaciones en las que colabora con Javier Tardáguila Laso (104)

2023

  1. Early yield prediction in different grapevine varieties using computer vision and machine learning

    Precision Agriculture, Vol. 24, Núm. 2, pp. 407-435

  2. Multi-sensor spectral fusion to model grape composition using deep learning

    Information Fusion, Vol. 99

  3. NIR attribute selection for the development of vineyard water status predictive models

    Biosystems Engineering, Vol. 229, pp. 167-178

2022

  1. Assessment of downy mildew in grapevine using computer vision and fuzzy logic. Development and validation of a new method

    Oeno One, Vol. 56, Núm. 3, pp. 41-53

  2. Combination of multispectral imagery, environmental data and thermography for on-the-go monitoring of the grapevine water status in commercial vineyards

    European Journal of Agronomy, Vol. 140

  3. Deep learning and computer vision for assessing the number of actual berries in commercial vineyards

    Biosystems Engineering, Vol. 218, pp. 175-188

2021

  1. Assessing actual number of grapevine berries using linear methods and machine learning

    PRECISION AGRICULTURE'21

  2. Assessing and mapping vineyard water status using a ground mobile thermal imaging platform

    Irrigation Science, Vol. 39, Núm. 4, pp. 457-468

  3. Monitoring and mapping vineyard water status using non-invasive technologies by a ground robot

    Remote Sensing, Vol. 13, Núm. 14

  4. Smart applications and digital technologies in viticulture: A review

    Smart Agricultural Technology, Vol. 1

2020

  1. 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 conditions

    Computers and Electronics in Agriculture, Vol. 178

2019

  1. A Non-Invasive Method Based on Computer Vision for Grapevine Cluster Compactness Assessment Using a Mobile Sensing Platform under Field Conditions

    Sensors (Basel, Switzerland), Vol. 19, Núm. 17

  2. Assessment of amino acids and total soluble solids in intact grape berries using contactless Vis and NIR spectroscopy during ripening

    Talanta, Vol. 199, pp. 244-253

  3. Hyperspectral imaging application under field conditions: Assessment of the spatio-temporal variability of grape composition within a vineyard

    Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019

  4. On-The-Go VIS + SW - NIR Spectroscopy as a Reliable Monitoring Tool for Grape Composition within the Vineyard

    Molecules (Basel, Switzerland), Vol. 24, Núm. 15

  5. On-the-go assessment of vineyard canopy porosity, bunch and leaf exposure by image analysis

    Australian Journal of Grape and Wine Research, Vol. 25, Núm. 3, pp. 363-374

  6. On-the-go hyperspectral imaging for the in-field estimation of grape berry soluble solids and anthocyanin concentration

    Australian Journal of Grape and Wine Research, Vol. 25, Núm. 1, pp. 127-133

  7. VINESCOUT: a vineyard autonomous robot for on-the-go assessment of grapevine vigour and water status [Poster]

    12th European Conference on Precision Agriculture, july 8-11, Montpellier, France. ECPA 2019

  8. Vineyard pruning weight assessment by machine vision: Towards an on-the-go measurement system

    Oeno One

2018

  1. Análisis del uso de datos geográficos y Sistemas de Información Geográfica en las enseñanzas de grado y máster de una universidad

    Actas de las Jornadas sobre la Enseñanza Universitaria de la Informática (JENUI), Núm. 3