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 . i6doc.com publication, BEL, pp. 489-496. ISBN 9782875870278

Full text not available from this repository.

Abstract

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.

Item Type:
Contribution in Book/Report/Proceedings
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1710
Subjects:
?? ARTIFICIAL INTELLIGENCEINFORMATION SYSTEMS ??
ID Code:
134273
Deposited By:
Deposited On:
22 Jun 2019 01:00
Refereed?:
Yes
Published?:
Published
Last Modified:
17 Sep 2023 04:04