Argitalpenak (50) JUAN IGNACIO ARRIBAS SANCHEZ argitalpenak

2023

  1. Contrastive Learning over Random Fourier Features for IoT Network Intrusion Detection

    IEEE Internet of Things Journal, Vol. 10, Núm. 10, pp. 8505-8513

  2. Examination of Lemon Bruising Using Different CNN-Based Classifiers and Local Spectral-Spatial Hyperspectral Imaging

    Algorithms, Vol. 16, Núm. 2

  3. From Harvest to Market: Non-Destructive Bruise Detection in Kiwifruit Using Convolutional Neural Networks and Hyperspectral Imaging

    Horticulturae, Vol. 9, Núm. 8

2022

  1. A predictive hybrid reduced order model based on proper orthogonal decomposition combined with deep learning architectures[Formula presented]

    Expert Systems with Applications, Vol. 187

  2. Metaheuristic algorithms in visible and near infrared spectra to detect excess nitrogen content in tomato plants

    Journal of Near Infrared Spectroscopy, Vol. 30, Núm. 4, pp. 197-207

  3. Supervised contrastive learning over prototype-label embeddings for network intrusion detection

    Information Fusion, Vol. 79, pp. 200-228

2021

  1. Additive ensemble neural network with constrained weighted quantile loss for probabilistic electric‐load forecasting

    Sensors, Vol. 21, Núm. 9

  2. Estimation of nitrogen content in cucumber plant (Cucumis sativus L.) leaves using hyperspectral imaging data with neural network and partial least squares regressions

    Chemometrics and Intelligent Laboratory Systems, Vol. 217

  3. Identification of internal defects in potato using spectroscopy and computational intelligence based on majority voting techniques

    Foods, Vol. 10, Núm. 5

  4. Network Intrusion Detection Based on Extended RBF Neural Network with Offline Reinforcement Learning

    IEEE Access, Vol. 9, pp. 153153-153170

  5. Network intrusion detection with a novel hierarchy of distances between embeddings of hash IP addresses

    Knowledge-Based Systems, Vol. 219

  6. Nondestructive estimation of three apple fruit properties at various ripening levels with optimal Vis-NIR spectral wavelength regression data

    Heliyon, Vol. 7, Núm. 9

  7. Nondestructive nitrogen content estimation in tomato plant leaves by Vis-NIR hyperspectral imaging and regression data models

    Applied Optics, Vol. 60, Núm. 30, pp. 9560-9569

  8. Novel data-driven models applied to short-term electric load forecasting

    Applied Sciences (Switzerland), Vol. 11, Núm. 12

2020

  1. A computer vision system based on majority-voting ensemble neural network for the automatic classification of three chickpea varieties

    Foods, Vol. 9, Núm. 2

  2. A computer vision system for the automatic classification of five varieties of tree leaf images

    Computers, Vol. 9, Núm. 1

  3. A three-variety automatic and non-intrusive computer vision system for the estimation of orange fruit pH value

    Measurement: Journal of the International Measurement Confederation, Vol. 152

  4. An automatic visible-range video weed detection, segmentation and classification prototype in potato field

    Heliyon, Vol. 6, Núm. 5

  5. Automatic non-destructive video estimation of maturation levels in Fuji apple (Malus Malus pumila) fruit in orchard based on colour (Vis) and spectral (NIR) data

    Biosystems Engineering, Vol. 195, pp. 136-151

  6. Non-destructive estimation of chlorophyll a content in red delicious apple cultivar based on spectral and color data

    Tarim Bilimleri Dergisi, Vol. 26, Núm. 3, pp. 339-348