Abstract:To tap-in the gold-mine of data generated by IoT devices with unprecedented volume and value, there is an urgent need to efficiently and accurately label raw sensor data. To this end, we explore and leverage the hidden connections among the multimodal data collected by various sensing devices, and propose to let different modal data complement and learn from each other. But it is challenging to align and fuse multimodal data without knowing their perception (and thus the correct labels). In this work, we propo… Show more
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