We are in the dawn of deep learning explosion for smartphones. To bridge the
gap between research and practice, we present the first empirical study on
16,500 the most popular Android apps, demystifying how smartphone apps exploit
deep learning in the wild. To this end, we build a new static tool that
dissects apps and analyzes their deep learning functions. Our study answers
threefold questions: what are the early adopter apps of deep learning, what do
they use deep learning for, and how do their deep learning models look like.
Our study has strong implications for app developers, smartphone vendors, and
deep learning R\&D. On one hand, our findings paint a promising picture of deep
learning for smartphones, showing the prosperity of mobile deep learning
frameworks as well as the prosperity of apps building their cores atop deep
learning. On the other hand, our findings urge optimizations on deep learning
models deployed on smartphones, the protection of these models, and validation
of research ideas on these models.

本研究通过针对 16,500 款最热门的 Android 应用程序的统计分析揭示了智能手机应用程序如何在自然环境中利用深度学习。研究发现，智能手机深度学习框架和应用程序的使用呈现出一种繁荣的趋势，但是仍需优化手机上运行的深度学习模型，保护这些模型并验证深度学习研究的想法。