Capítulos de Libro

De Grupo de Inteligencia Computacional (GIC)

2024

  1. Cano-Escalera, G., Graa, M., MacDowell, K.S., Leza, J.C., Zorilla, I., Gonzlez-Pinto, A. (2025). Machine Learning for the Identification of Biomarker and Risk Factors associated with Depression in Adult Population: Preliminary Results on a Small Cohort. In: Quintián, H., et al. Hybrid Artificial Intelligent Systems. HAIS 2024. Lecture Notes in Computer Science(), vol 14857. Springer, Cham. https://doi.org/10.1007/978-3-031-74183-8_4
  3. Graña, M., Badiola-Zabala, G., Cano-Escalera, G. (2024). Topic Detection in COVID-19 Mortality Time Series. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Bioinspired Systems for Translational Applications: From Robotics to Social Engineering. IWINAC 2024. Lecture Notes in Computer Science, vol 14675. Springer, Cham. https://doi.org/10.1007/978-3-031-61137-7_33
  5. Razi, M., Graña, M. (2024). Clustering COVID-19 Mortality Time Series. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Bioinspired Systems for Translational Applications: From Robotics to Social Engineering. IWINAC 2024. Lecture Notes in Computer Science, vol 14675. Springer, Cham. https://doi.org/10.1007/978-3-031-61137-7_38
  7. Morais-Quilez, I., Graña, M., de Lope, J. (2024). Machine Learning for Personality Type Classification on Textual Data. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Artificial Intelligence for Neuroscience and Emotional Systems. IWINAC 2024. Lecture Notes in Computer Science, vol 14674. Springer, Cham. https://doi.org/10.1007/978-3-031-61140-7_26
  9. Estevez, J., Caballero-Martin, D., Lopez-Guede, J.M., Graña, M. (2024). A Decentralized Collision Avoidance Algorithm for Individual and Collaborative UAVs. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Bioinspired Systems for Translational Applications: From Robotics to Social Engineering. IWINAC 2024. Lecture Notes in Computer Science, vol 14675. Springer, Cham. https://doi.org/10.1007/978-3-031-61137-7_2
  11. Caballero-Martin, D., Lopez-Guede, J.M., Estevez, J., Graña, M. (2024). AI Emmbedded in Drone Control. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Bioinspired Systems for Translational Applications: From Robotics to Social Engineering. IWINAC 2024. Lecture Notes in Computer Science, vol 14675. Springer, Cham. https://doi.org/10.1007/978-3-031-61137-7_19
  13. Kerexeta, J. et al. (2024). Multicenter Prospective Blind External Validation of a Machine Learning Model for Predicting Heart Failure Decompensation: A 3-Hospital Validation Study. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Bioinspired Systems for Translational Applications: From Robotics to Social Engineering. IWINAC 2024. Lecture Notes in Computer Science, vol 14675. Springer, Cham. https://doi.org/10.1007/978-3-031-61137-7_34
  15. Aravena-Cifuentes, A.P., Porlan-Ferrando, L., Nuñez-Gonzalez, J.D., Graña, M. (2024). Brainstorming on Dataset Reduction from an Heuristic Bioinspired Green Computing Approach. In: Ferrández Vicente, J.M., Val Calvo, M., Adeli, H. (eds) Bioinspired Systems for Translational Applications: From Robotics to Social Engineering. IWINAC 2024. Lecture Notes in Computer Science, vol 14675. Springer, Cham. https://doi.org/10.1007/978-3-031-61137-7_41
  17. G. Badiola and M. Graña, "Wavelet Coherence of COVID-19 Pandemic Variables in Japan," 2024 16th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), Takamatsu, Japan, 2024, pp. 379-384, doi: 10.1109/IIAI-AAI63651.2024.00076.

keywords: {COVID-19;Time-frequency analysis;Correlation;Pandemics;Time series analysis;Optical wavelength conversion;Coherence;Wavelet analysis;Time measurement;Vaccines;COVID-19;epidemiological analysis;wavelet coherence},

2023

  1. Aguilar-Moreno, M., Graña, M. (2023). Computational Ethology: Short Review of Current Sensors and Artificial Intelligence Based Methods. In: Iliadis, L., Maglogiannis, I., Alonso, S., Jayne, C., Pimenidis, E. (eds) Engineering Applications of Neural Networks. EANN 2023. Communications in Computer and Information Science, vol 1826. Springer, Cham. https://doi.org/10.1007/978-3-031-34204-2_2
  3. Aguilar-Moreno, M., Graña, M. (2023). Phenotype Discrimination Based on Pressure Signals by Transfer Learning Approaches. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2023. Lecture Notes in Computer Science, vol 14135. Springer, Cham. https://doi.org/10.1007/978-3-031-43078-7_12
  5. Lopez-Guede, J.M. et al. (2023). Educational Innovation Project in the Field of Informatics. In: García Bringas, P., et al. International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023). CISIS ICEUTE 2023 2023. Lecture Notes in Networks and Systems, vol 748. Springer, Cham. https://doi.org/10.1007/978-3-031-42519-6_33
  7. Alawneh, H., David Nuñez-Gonzalez, J., Graña, M. (2023). Exploring Delay Reduction on Edge Computing Architectures from a Heuristic Approach. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham. https://doi.org/10.1007/978-3-031-40725-3_11
  9. Muñoz-Cancino, R., Ríos, S.A., Graña, M. (2023). Predicting Innovative Cities Using Spatio-Temporal Activity Patterns. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham. https://doi.org/10.1007/978-3-031-40725-3_48
  11. Cano-Escalera, G., Grana, M., Besga, A. (2023). Risk Factors and Survival After Premature Hospital Readmission in Frail Subjects with Delirium. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham. https://doi.org/10.1007/978-3-031-40725-3_59
  13. Badiola, G., Grana, M., Lopez-Guede, J.M. (2023). Coherence of COVID-19 Mortality of Spain Versus Western European Countries. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham. https://doi.org/10.1007/978-3-031-40725-3_61
  15. Garmendia-Orbegozo, A., Nuñez-Gonzalez, J.D., Anton Gonzalez, M.A., Graña, M. (2023). Comprehensive Analysis of Different Techniques for Data Augmentation and Proposal of New Variants of BOSME and GAN. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham. https://doi.org/10.1007/978-3-031-40725-3_13

2022

  1. Baterdene Batmunkh, Jose Antonio Chica Paez, Sergio Gil Lopez, Maider Arana Bollar, Oihana Jauregi Zorzano, Andoni Aranguren Ubierna, Manuel Graña, and J. David Nuñez-Gonzalez (2023). First Steps Predicting Execution of Civil Works from Georeferenced Infrastructure Data. In: , et al. 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022). SOCO 2022. Lecture Notes in Networks and Systems, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-031-18050-7_19
  2. Morais-Quilez, I., Graña, M. (2023). Identification of Critical Subgraphs in Drone Airways Graphs by Graph Convolutional Networks. In: , et al. 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022). SOCO 2022. Lecture Notes in Networks and Systems, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-031-18050-7_43
  4. Badiola-Zabala, G., Lopez-Guede, J.M., Estevez, J., Graña, M. (2022). Triage Prediction of a Real Dataset of COVID-19 Patients in Alava. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence. IWINAC 2022. Lecture Notes in Computer Science, vol 13259. Springer, Cham. https://doi.org/10.1007/978-3-031-06527-9_47
  6. Badiola-Zabala, G., Lopez-Guede, J.M., Estevez, J., Graña, M. (2022). On the Analysis of a Real Dataset of COVID-19 Patients in Alava. In: , et al. Hybrid Artificial Intelligent Systems. HAIS 2022. Lecture Notes in Computer Science(), vol 13469. Springer, Cham. https://doi.org/10.1007/978-3-031-15471-3_5
  8. Rebollar, I.S., Graña, M. (2022). Deep Learning Artwork Style Prediction and Similarity Detection. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence. IWINAC 2022. Lecture Notes in Computer Science, vol 13259. Springer, Cham. https://doi.org/10.1007/978-3-031-06527-9_28
  10. Muñoz-Cancino, R., Bravo, C., Ríos, S.A., Graña, M. (2022). Assessment of Creditworthiness Models Privacy-Preserving Training with Synthetic Data. In: , et al.Hybrid Artificial Intelligent Systems. HAIS 2022. Lecture Notes in Computer Science(), vol 13469. Springer, Cham. https://doi.org/10.1007/978-3-031-15471-3_32
  12. Cano-Escalera, G., Graña, M., Besga, A. (2022). Frailty Related Survival Risks at Short and Middle Term of Older Adults Admitted to Hospital. In: , et al. Hybrid Artificial Intelligent Systems. HAIS 2022. Lecture Notes in Computer Science(), vol 13469. Springer, Cham. https://doi.org/10.1007/978-3-031-15471-3_4
  14. Nicolás, J.A., de Lope, J., Graña, M. (2022). Data Augmentation Techniques for Speech Emotion Recognition and Deep Learning. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence. IWINAC 2022. Lecture Notes in Computer Science, vol 13259. Springer, Cham. https://doi.org/10.1007/978-3-031-06527-9_27

2021

  1. Graña, M., Badiola-Zabala, G., Lopez-Guede, J.M. (2021). Counter Intituive COVID-19 Propagation Dynamics in Brazil. In: Sanjurjo González, H., Pastor López, I., García Bringas, P., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2021. Lecture Notes in Computer Science(), vol 12886. Springer, Cham. https://doi.org/10.1007/978-3-030-86271-8_36
  2. Silva, M., Graña, M. (2022). On Machine Learning for Autism Prediction from Functional Connectivity. In: Choraś, M., Choraś, R.S., Kurzyński, M., Trajdos, P., Pejaś, J., Hyla, T. (eds) Progress in Image Processing, Pattern Recognition and Communication Systems. CORES IP&C ACS 2021 2021 2021. Lecture Notes in Networks and Systems, vol 255. Springer, Cham. https://doi.org/10.1007/978-3-030-81523-3_16
  3. de Lope, J., Hernández, E., Vargas, V., Graña, M. (2021). Speech Emotion Recognition by Conventional Machine Learning and Deep Learning. In: Sanjurjo González, H., Pastor López, I., García Bringas, P., Quintián, H., Corchado, E. (eds) Hybrid Artificial Intelligent Systems. HAIS 2021. Lecture Notes in Computer Science(), vol 12886. Springer, Cham. https://doi.org/10.1007/978-3-030-86271-8_27
  4. Alonso, M., Izaguirre, A., Andonegui, I., Graña, M. (2021). An Application of Laser Measurement to On-Line Metal Strip Flatness Measurement. In: Herrero, Á., Cambra, C., Urda, D., Sedano, J., Quintián, H., Corchado, E. (eds) 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020). SOCO 2020. Advances in Intelligent Systems and Computing, vol 1268. Springer, Cham. https://doi.org/10.1007/978-3-030-57802-2_80
  5. Aristondo, O., Nuñez-Gonzalez, J.D., Graña, M. (2021). Introducing Active Methodologies in Renewable Energy Engineering Bachelor in Mathematical and Numerical Analysis Subject. In: Herrero, Á., Cambra, C., Urda, D., Sedano, J., Quintián, H., Corchado, E. (eds) The 11th International Conference on EUropean Transnational Educational (ICEUTE 2020). ICEUTE 2020. Advances in Intelligent Systems and Computing, vol 1266. Springer, Cham. https://doi.org/10.1007/978-3-030-57799-5_12
  6. Estevez, J., Garate, G., Lopez-Guede, J.M., Graña, M. (2021). Expansion of an Evidence-Based Workshop for Teaching of Artificial Intelligence in Schools. In: Herrero, Á., Cambra, C., Urda, D., Sedano, J., Quintián, H., Corchado, E. (eds) The 11th International Conference on EUropean Transnational Educational (ICEUTE 2020). ICEUTE 2020. Advances in Intelligent Systems and Computing, vol 1266. Springer, Cham. https://doi.org/10.1007/978-3-030-57799-5_34
  7. Aguilar-Moreno, M., Graña, M. (2021). A Comparison of Registration Methods for SLAM with the M8 Quanergy LiDAR. In: Herrero, Á., Cambra, C., Urda, D., Sedano, J., Quintián, H., Corchado, E. (eds) 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020). SOCO 2020. Advances in Intelligent Systems and Computing, vol 1268. Springer, Cham. https://doi.org/10.1007/978-3-030-57802-2_79
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