We explore what happens in the increasingly likely situation that a robot has sensed information about a child of which the child is unaware, then discloses that information in conversation in an effort to personalize the child’s experience.
We propose the notion of semi-supervised vocabulary-informed learning to alleviate the above mentioned challenges and address problems of supervised, zero-shot and open set recognition using a unified framework.
In this work we improve training of temporal deep models to better learn activity progression for activity detection and early detection tasks.
We propose a novel object- and scene-based semantic fusion network and representation.
We propose a recurrent decision tree framework that can directly incorporate temporal consistency into a data-driven predictor, as well as a learning algorithm that can efficiently learn such temporally smooth models.
Energy-harvesting computers eschew tethered power and batteries by harvesting energy from their environment.
This paper presents the NFC-WISP, which is a programmable, sensing and computationally enhanced platform designed to explore new RFID enabled sensing and user interface applications.
In this paper, we propose an unexplored type of wireless power transfer system based on electromagnetic cavity resonance.
This paper proposes using the electromagnetic resonant modes of a hollow metallic structure to provide wireless power to small receivers contained anywhere inside.
In this work we propose ‘mean time between failures’ as a viable summary of solution quality - especially when the goal is to follow objects for as long as possible.
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