Poster: Towards condition-independent deep mobile sensing

Abstract

Deep mobile sensing applications are suffering from various individual conditions in the wild. We propose a meta-learned adaptation technique to adapt to a target condition with a few labeled data. We evaluate our system on a public dataset and it outperforms baselines.