Advances and Challenges of Deep Learning

Shui Hua Wang, Yu Dong Zhang*

*Corresponding author for this work

Research output: Contribution to journalEditorial

5 Citations (Scopus)


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.

Original languageEnglish
Article numbere300522205402
JournalRecent Patents on Engineering
Issue number4
Publication statusPublished - 1 Jul 2023
Externally publishedYes


  • Artificial intelligence
  • COVID-19 diagnosis
  • deep learning
  • deep mind ANNs
  • machine learning


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