Mobile sensing through deep learning

4Citations
Citations of this article
15Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Today, mobile devices are equipped with powerful processors along with various on-device sensors. Over the past few years, deep learning has become the dominant approach in the field of machine learning due to its impressive performance. We envision that in the near future, powered by deep learning, mobile devices will become more intelligent and revolutionize a wide range of applications. In this paper, we discuss the challenges of enabling deep learning on mobile platforms. Our work is to propose a deep learning framework that achieves state-of-the-art performance with low overhead on resource-limited mobile platforms. Our preliminary results show that deep learning can efficiently solve object recognition problem under noisy real world environment.

Cite

CITATION STYLE

APA

Zeng, X. (2017). Mobile sensing through deep learning. In MobiSys 2017 PhD Forum - Proceedings of the 2017 Workshop on MobiSys 2017 Ph.D. Forum, co-located with MobiSys 2017 (pp. 5–6). Association for Computing Machinery. https://doi.org/10.1145/3086467.3086476

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free