- ISSN: 1872-2121
- E-ISSN: 2212-4047
-
s Advances and Challenges of Deep Learning
- Source: Recent Patents on Engineering, Volume 17, Issue 4, Jul 2023, p. 1 - 2
-
- 01 Jul 2023
Abstract
This editorial presents the recent advances and challenges of deep learning. We reviewed four main challenges: heterogeneity, copious size, reproducibility crisis, and explainability. Finally, we present the prospect of deep learning in industrial applications.
© Bentham Science Publishers
