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The authors explore various applications that can be enabled by transforming mobile devices into active sonar systems. Specifically, they show how to use microphones and speakers available on existing smartphones to monitor minute body movements such as breathing. Using this, they build systems that will demonstrate the feasibility of achieving contactless solutions for sleep apnea diagnosis. Building...
This department provides an overview the progress the authors have made to the emerging area of embedded and mobile forms of on-device deep learning. Their work addresses two core technical questions. First, how should deep learning principles and algorithms be applied to sensor inference problems that are central to this class of computing? Second, what is required for current and future deep learning...
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