Argitalpenak (199) Javier Tardáguila Laso argitalpenak

2024

  1. Deep learning modelling for non-invasive grape bunch detection under diverse occlusion conditions

    Computers and Electronics in Agriculture, Vol. 226

  2. Image analysis with deep learning for early detection of downy mildew in grapevine

    Scientia Horticulturae, Vol. 331

  3. In-field disease symptom detection and localisation using explainable deep learning: Use case for downy mildew in grapevine

    Computers and Electronics in Agriculture, Vol. 226

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. Evolutionary conditional GANs for supervised data augmentation: The case of assessing berry number per cluster in grapevine

    Applied Soft Computing, Vol. 147

  3. Inteligencia artificial y visión por ordenador para evaluar los componentes del rendimiento de la vid en viñedos comerciales

    BIO Web of Conferences: 44th World Congress of Vine and Wine

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

    Information Fusion, Vol. 99

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

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

  6. Using artificial intelligence (AI) for grapevine disease detection based on images

    BIO Web of Conferences: 44th World Congress of Vine and Wine

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

  4. Low-Cost Electronic Nose for Wine Variety Identification through Machine Learning Algorithms

    Agronomy, Vol. 12, Núm. 11

  5. Message from the Technical Program Chairs

    2022 IEEE Workshop on Metrology for Agriculture and Forestry, MetroAgriFor 2022 - Proceedings

2021

  1. Aplicación de la visión por computador para evaluar la canopy en viñedos comerciales

    La Semana vitivinícola, Núm. 3605, pp. 1991-1994

  2. Aplicación de la visión por computador para evaluar la canopy en viñedos comerciales

    La Semana vitivinícola, Núm. 3589, pp. 468-471

  3. Artificial intelligence and novel sensing technologies for assessing downy mildew in grapevine

    Horticulturae, Vol. 7, Núm. 5

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

    PRECISION AGRICULTURE'21

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

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

  6. Deep learning for the differentiation of downy mildew and spider mite in grapevine under field conditions

    Computers and Electronics in Agriculture, Vol. 182