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Dr E. Hortal Quesada

Publications

Most recent publications:

  • García Fernández, J., Hortal, E., & Mehrkanoon, S. (2021). Towards biologically plausible learning in neural networks. In 2021 IEEE Symposium Series on Computational Intelligence (SSCI) (pp. 1-8). [9659539] IEEE Canada. https://doi.org/10.1109/SSCI50451.2021.9659539

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  • Bhat, S., & Hortal, E. (2021). GAN-Based Data Augmentation For Improving The Classification Of EEG Signals. In 14th PErvasive Technologies Related to Assistive Environments Conference (PETRA 2021) (pp. 453-458). Association for Computing Machinery. https://doi.org/10.1145/3453892.3461338

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  • Athanasiadis, C., Hortal, E., & Asteriadis, S. (2021). Temporal conditional Wasserstein GANs for audio-visual affect-related ties. In 2021 9th International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW) (pp. 1-8) https://doi.org/10.1109/ACIIW52867.2021.9666277

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  • Standen, P. J., Brown, D. J., Taheri, M., Trigo, M. J. G., Boulton, H., Burton, A., Hallewell, M. J., Lathe, J. G., Shopland, N., Gonzalez, M. A. B., Kwiatkowska, G. M., Milli, E., Cobello, S., Mazzucato, A., Traversi, M., & Hortal, E. (2020). An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities. British Journal of Educational Technology, 51(5), 1748-1765. https://doi.org/10.1111/bjet.13010

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  • Athanasiadis, C., Hortal, E., & Asteriadis, S. (2020). Audio–visual domain adaptation using conditional semi-supervised Generative Adversarial Networks. Neurocomputing, 397, 331-344. https://doi.org/10.1016/j.neucom.2019.09.106

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  • Athanasiadis, C., Hortal, E., & Asteriadis, S. (2020). Audio-Based Emotion Recognition Enhancement Through Progressive GANS. In 2020 IEEE International Conference on Image Processing (ICIP) (pp. 236-240). IEEE. https://ieeexplore.ieee.org/document/9190959

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  • Athanasiadis, C., Amestoy, M., Hortal, E., & Asteriadis, S. (2020). e3Learning: A Dataset for Affect-Driven Adaptation of Computer-Based Learning. Ieee Multimedia, 27(1), 49-60. https://doi.org/10.1109/mmul.2019.2945716

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  • Vretos, N., Daras, P., Asteriadis, S., Hortal, E., Ghaleb, E., Spyrou, E., Leligou, H. C., Karkazis, P., Trakadas, P., & Assimakopoulos, K. (2019). Exploiting sensing devices availability in AR/VR deployments to foster engagement. Virtual Reality, 23(4), 399-410. https://doi.org/10.1007/s10055-018-0357-0

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  • Athanasiadis, C., Hortal, E., & Asteriadis, S. (2019). Bridging face and sound modalities through Domain Adaptation Metric Learning. In ESANN 2019 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges (Belgium), 24-26 April 2019 (pp. 385-390) https://www.elen.ucl.ac.be/Proceedings/esann/esannpdf/es2019-143.pdf

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  • Tsatsou, D., Pomazanskyi, A., Hortal, E., Spyrou, E., Leligou, H. C., Asteriadis, S., Vretos, N., & Daras, P. (2018). Adaptive Learning Based on Affect Sensing. In R. C. Penstein (Ed.), Artificial Intelligence in Education. AIED 2018 (pp. 475-479). Springer, Cham. Lecture Notes in Computer Science Vol. 10948 https://doi.org/10.1007/978-3-319-93846-2_89

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https://www.researchgate.net/profile/Enrique_Hortal

E. Hortal Quesada

Assistant professor

Dept. of Advanced Computing Sciences, Faculty of Science and Engineering
ORCID
enrique​.​hortal​@​​maastricht​university​.​nl
+31(0)43 3883902
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E. Hortal Quesada

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