Formal methods enhance deep learning for smart cities: Challenges and future directions

被引：0

作者：

Ma, Meiyi ^{[1
]}

机构：

[1] Department of Computer Science, Vanderbilt University, United States

来源：

XRDS: Crossroads | 2022年 / 28卷 / 03期

关键词：

Deep learning - Smart city;

D O I：

10.1145/3522694

中图分类号：

学科分类号：

摘要：

Rigorous approaches based on formal methods have the potential to fundamentally improve many aspects of deep learning. This article discusses the challenges and future directions of formal methods enhanced deep learning for smart cities. © 2022 ACM.

引用

页码：42 / 46