TAR3-ARFAI + Consolider MIPRCV + TAR4-TIASA Projects

PUBLICATIONS (2014 - 2019)

    2019

    1. B. Nguyen, F.J. Ferri, C. Morell, B. De Baets. An efficient method for clustered multi-metric learning. Information Sciences, Vol. 471, pp. 149-163, 2019. {https://doi.org/10.1016/j.ins.2018.08.055}
    2. H. Gonzalez, C. Morell and F.J. Ferri. Aprendizaje de funciones de distancia para problemas de predicción con salidas múltiples mediante gradiente estocástico. CIPI'19, Convención Internacional de la UCLV, 2019. {url-1535}
    3. M. Arevalillo, F.J. Ferri, G. Chicote,A. Ayesh, J.G. Boticario, P. Arnau, N. Ramzan. On using EEG signals for emotion modeling and biometry, ESM'19, 2019, {}
    4. I. Martin-Morato, M. Cobos, F.J. Ferri, J. Naranjo-Alcázar. Performance Analysis of Audio Event Classification Using Deep Features under Adverse Acoustic Conditions. ICA'19, 2019. {http://app.ica2019.org/konferenz?article=667}
    5. I. Martín-Morató, A. Mesaros, T. Heittola, T. Virtanen, M. Cobos, F.J. Ferri. Sound Event Envelope Estimation in Polyphonic Mixtures. ICASSP'19, pp. 935-939, 2019. {https://doi.org/10.1109/ICASSP.2019.8682858}
    6. S. Moreno-Picot, F.J. Ferri, M. Arevalillo-Herráez, W. Díaz-Villanueva. Efficient Analysis and Synthesis using a New Factorization of the Gabor Frame Matrix. ICASSP'19, accepted, 2019. {https://cmsworkshops.com/ICASSP2019/Papers/ViewPapers.asp?PaperNum=5372}

      2018

    1. H. Gonzalez, C. Morell, F.J. Ferri. Generalized Multitarget Linear Regression with Output Dependence Estimation, CIARP'18, R. Vera-Rodriguez et al., eds). Lect. Not in Comp Sci. Vol 11401, pp. 1-9, 2019. {https://doi.org/10.1007/978-3-030-13469-3_35}
    2. H. Gonzalez, C. Morell, F.J. Ferri. Accelerated proximal gradient descent in metric learning for kernel regression, IWAIPR'18, Progress in Artificial Intelligence and Pattern Recognition, Y. Hernández Heredia et al. (Eds.) LNCS 11047, pp. 219-227, 2018. {https://doi.org/10.1007/978-3-030-01132-1_25}
    3. I. Martin-Morato, M. Cobos, F.J. Ferri, Adaptive Mid-term Representations for Robust Audio Event Detection. IEEE/ACM Trans. on Audio, Speech and Language Processing, Vol.26, No.12, pp. 2381-2392, 2018. {https://doi.org/10.1109/TASLP.2018.2865615}
    4. S. Moreno-Picot, F.J. Ferri, M. Arevalillo, W. Diaz-Villanueva. Efficient Analysis and Synthesis using a New Factorization of the Gabor Frame Matrix. IEEE Trans. on Signal Processing, Vol.66, No.17, pp. 4564-4573, 2018. {http://dx.doi.org/10.1109/TSP.2018.2855643}
    5. R. Cabestrero, P. Quiros, O. Santos, S. Salmeron, R. Uria, J.G. Boticario, D. Arnau, M. Arevalillo, F.J. Ferri, Some Insights into the Impact of Affective Information when Delivering Feedback to Students. Behaviour & Information Technology, Vol. 37, No. 12, pp.1252-1263, 2018. {http://dx.doi.org/10.1080/0144929X.2018.1499803}
    6. I. Martin-Morato, M. Cobos, F.J. Ferri. On the Robustness of Deep Features for Audio Event Classification in Adverse Environments, IEEE ICSP'18. pp. 562-566, 2018. {https://doi.org/10.1109/ICSP.2018.8652438}
    7. K. Diaz-Chito, J. Martinez del Rincon, A. Hernandez-Sabate, M. Rusiñol and F.J. Ferri. Fast Kernel Generalized Discriminative Common Vectors for Featue Extraction, Journal of Mathematical Imaging and Vision, Vol.60, No.4, pp.512-524, 2018. {http://dx.doi.org/10.1007/s10851-017-0771-z}
    8. K. Diaz-Chito, F.J. Ferri, A. Hernandez-Sabate. An Overview of Incremental Feature Extraction Methods based on Linear Subspaces, Knowledge-based Systems, Vol. 145, April, pp. 219-235, 2018. {http://dx.doi.org/10.1016/j.knosys.2018.01.020}

      9. 2017

    1. M. Arevalillo, D. Arnau, F.J. Ferri and O.C. Santos. GUI-driven Intelligent Tutoring System with Affective Support to Help Learning the Algebraic Method, IEEE Conf on Syst, Man and Cybernetics (SMC 2017), pp.2867-2872, 2017. {http://dx.doi.org/10.1109/SMC.2017.8123062}
    2. M. Sanz, D. Arnau, J.A. Gonzalez-Calero, F.J. Ferri, M. Arevalillo-Herraez. Predicting Human Performance in Interactive Tasks by using Dynamic Models, IEEE Conf on Syst, Man and Cybernetics (SMC 2017), pp.776-780, 2017. {http://dx.doi.org/10.1109/SMC.2017.8122702}
    3. Boticario, J. G., Santos, O. C., Salmeron-Majadas, S., Uria-Rivas, R., Saneiro, M., Cabestrero, R., Quirós, P., Arevalillo-Herraez, M., Ferri, F. J.,  BIG-AFF: Exploring Low Cost and Low Intrusive Infrastructures for Affective Computing in Secondary Schools , UMAP 2017 (PALE Workshop), ACM proceedings, pp 287-292, 2017. {http://dx.doi.org/10.1145/3099023.3099084}
    4. H. Gonzalez, C. Morell, F.J. Ferri. Regularización basado en Elastic Net para problemas de predicción con salidas múltiples. Convención UCLV, CIPI'17. paper 20, 2017. {}
    5. I. Martín-Morató, M. Cobos, F.J. Ferri. Analysis of Data Fusion Techniques for Multi-Microphone Audio Event Detection in Adverse Environments, IEEE Intl. Workshop on Multimedia Signal Processing (MMSP 2017), pp 1-6, 2017. {http://dx.doi.org/10.1109/MMSP.2017.8122274}
    6. I. Martín-Morató, M. Cobos, F.J. Ferri, J. Segura. Estudio de sensibilidad de las características para la detección de eventos acústicos utilizando máquinas de vectores soporte, 48 Congreso Español de Acustica (TecniAcustica 2017), 43.60.Np.001, 2017. {http://www.sea-acustica.es/fileadmin/publicaciones/AAM-6_002_03.pdf}

      2016

    1. A. Ayesh, M. Arevalillo, F.J. Ferri. Towards Psychologically based Personalised Modelling of Emotions Using Associative Classifiers, International Journal of Cognitive Informatics and Natural Intelligence, Vol. 10, No. 2, 2016. {http://dx.doi.org/10.4018/IJCINI.2016040103}
    2. H. Gonzalez, C. Morell, F.J. Ferri, Improving Nearest Neighbor based Multi-Target Prediction through Metric Learning, CIARP 2016, C. Beltrán, I. Nyström, F. Famili (eds). Lect. Not in Comp Sci. Vol 10125, pp.368-376, 2016 {https://doi.org/10.1007/978-3-319-52277-7_45}.
    3. I. Martín-Morató, M. Cobos, F.J. Ferri. A Case Study on Feature Sensitivity for Audio Event Classification using Support Vector Machines, IEEE Intl. Workshop on Machine Learning for Signal Processing (MLSP 2016), pp 1-6, 2016. {http://dx.doi.org/10.1109/MLSP.2016.7738834}
    4. Gimenez, L. M., Arevalillo-Herraez, M., Ferri, F. J., Boticario, J. G., Santos, O. C., Salmeron-Majadas, S., Saneiro, M., Uria-Rivas, R., Moreno-Picot, S., Arnau, D., Gonzalez-Calero, J. A., Ayesh, A., Cabestrero, R., Quirps, P., Arnau-Gonzalez, P., and Ramzan, N. Affective and behavioral assessment for adaptive intelligent tutoring systems, UMAP 2016 (PALE Workshop), Ceur Workshop, Vol 1618, pp 17-21, 2016. {http://ceur-ws.org/Vol-1618/PALE3.pdf}

      2015

    1. K. Diaz-Chito and F.J. Ferri and W. Díaz-Villanueva. Incremental Generalized Discriminative Common Vectors for Image Classification. IEEE Trans. on Neural Networks and Learning Systems, Vol. 26, No. 8, pp. 1761-1775, 2015. {http://dx.doi.org/10.1109/TNNLS.2014.2356856} 
    2. M. Arevalillo and F.J. Ferri and S. Moreno-Picot. Improving distance based image retrieval using non-dominated sorting genetic algorithm. Pattern Recognition Letters,  Vol. 53, pp. 109-117, 2015. {http://dx.doi.org/10.1016/j.patrec.2014.05.008}
    3. A. Pérez-Suay, F.J. Ferri, M. Arevalillo-Herraez, J.V. Albert. An Empirical Study about Online Learning with Generalized Passive-aggressive approaches, CAEPIA'15 (TAMIDA Workshop), Accepted, 2015.

      4. 2014

    4. A. Pérez-Suay, F.J. Ferri, M. Arevalillo-Herraez, J.V. Albert. About Combining Metric Learning and Prototype Generation. SSSPR'14. Structural, Syntactic and Statistical Pattern Recognition.  P. Franti et al. (eds). Lect. Not in Comp Sci. Vol 8621, pp.323-332, 2014. {http://dx.doi.org/10.1007/978-3-662-44415-3_33}
    5. M. Arevalillo and F.J. Ferri and S. Moreno-Picot. Improving distance based image retrieval using non-dominated sorting genetic algorithm. SSSPR'14. Structural, Syntactic and Statistical Pattern Recognition.  P. Franti et al. (eds). Lect. Not in Comp Sci. Vol 8621, pp., 2014. {http://dx.doi.org/10.1007/978-3-662-44415-3}
    6. A. Ayesh, M. Arevalillo-Herráez, F. J. Ferri. Psychologically based Personalised Modelling of Emotions Using Associative Classifiers. ICCI'14. 13th IEEE Intl. Conf. on Cognitive Informatics and Cognitive Computing, pp. 67-72, 2014. {http://dx.doi.org/10.1109/ICCI-CC.2014.6921443}{ieeexpl}

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