Challenges in deep learning

Angelov, Plamen and Sperduti, Alessandro (2016) Challenges in deep learning. In: ESANN 2016 - 24th European Symposium on Artificial Neural Networks. ESANN 2016 - 24th European Symposium on Artificial Neural Networks . publication, BEL, pp. 489-496. ISBN 9782875870278

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In recent years, Deep Learning methods and architectures have reached impressive results, allowing quantum-leap improvements in performance in many difficult tasks, such as speech recognition, end-to-end machine translation, image classification/understanding, just to name a few. After a brief introduction to some of the main achievements of Deep Learning, we discuss what we think are the general challenges that should be addressed in the future. We close with a review of the contributions to the ESANN 2016 special session on Deep Learning.

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22 Jun 2019 01:00
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21 Nov 2022 16:55