Dong-Hyun Kwak

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Deep neural networks continue to advance the state-of-the-art of image recognition tasks with various methods. However, applications of these methods to multimodality remain limited. We present Multimodal Residual Networks (MRN) for the multimodal residual learning of visual question-answering, which extends the idea of the deep residual learning. Unlike(More)
Learning from human behaviors in the real world is important for building human-aware intelligent systems such as personalized digital assistants and autonomous humanoid robots. Everyday activities of human life can now be measured through wearable sensors. However, innovations are required to learn these sensory data in an online in-cremental manner over(More)
Wearable devices, such as smart glasses and watches, allow for continuous recording of everyday life in a real world over an extended period of time or lifelong. This possibility helps better understand the cognitive behavior of humans in real life as well as build human-aware intelligent agents for practical purposes. However, modeling the human cognitive(More)
—This paper introduces Glassbot, the agent on glass-type wearable devices with camera and audio sensors. We want to train Glassbot continuously in a wearable device by rapidly adapting deep neural networks from sensor data streams of user behaviors. In this paper, we describe our early works on dataset and online learning algorithms for Glassbot. We also(More)