LUIS JAVIER HERRERA MALDONADO-rekin lankidetzan egindako argitalpenak (85)

2023

  1. Speeding up Simulations for Radiotherapy Research by Means of Machine Learning

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2022

  1. Gene Expression Tools from a Technical Perspective: Current Approaches and Alternative Solutions for the KnowSeq Suite

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2021

  1. Adoption of electric vehicles: Which factors are really important?

    International Journal of Sustainable Transportation, Vol. 15, Núm. 10, pp. 799-813

  2. Comparison of Fusion Methodologies Using CNV and RNA-Seq for Cancer Classification: A Case Study on Non-Small-Cell Lung Cancer

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Deep learning to classify ultra-high-energy cosmic rays by means of PMT signals

    Neural Computing and Applications, Vol. 33, Núm. 15, pp. 9153-9169

  4. Non-small-cell lung cancer classification via RNA-Seq and histology imaging probability fusion

    BMC Bioinformatics, Vol. 22, Núm. 1

2020

  1. A comparative analysis of machine learning techniques for Muon count in uhecr extensive air-showers

    Entropy, Vol. 22, Núm. 11, pp. 1-17

  2. Composition classification of ultra-high energy cosmic rays

    Entropy, Vol. 22, Núm. 9

  3. Using Convolutional Neural Networks for Muon detection in WCD tank

    Journal of Physics: Conference Series

2019

  1. A preliminary approach to composition classification of ultra-high energy cosmic rays

    Lecture Notes in Electrical Engineering

  2. Improving Classification of Ultra-High Energy Cosmic Rays Using Spacial Locality by Means of a Convolutional DNN

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Improving Wearable Activity Recognition via Fusion of Multiple Equally-Sized Data Subwindows

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2017

  1. Combination of EEG data time and frequency representations in deep networks for sleep stage classification

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Deep learning using EEG data in time and frequency domains for sleep stage classification

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10305 LNCS, pp. 132-141

2016

  1. Decision Support System to Determine Intention to Use Mobile Payment Systems on Social Networks: A Methodological Analysis

    International Journal of Intelligent Systems, Vol. 31, Núm. 2, pp. 153-172

  2. Variable selection for payment in social networks: Introducing the Hy-index

    Computers in Human Behavior, Vol. 56, pp. 45-55

2015

  1. Modeling the EUR/USD index using LS-SVM and performing variable selection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Multi-sensor Fusion Based on Asymmetric Decision Weighting for Robust Activity Recognition

    Neural Processing Letters, Vol. 42, Núm. 1, pp. 5-26

  3. Multiwindow fusion for wearable activity recognition

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  4. Mutual information-based feature selection in spectrometric data for agriculture applications

    Lecture Notes in Engineering and Computer Science