We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
Research in Ambient Intelligence and Ubiquitous Computing has put computational devices into many social settings while leaving intact much of the "task support and informati...
Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference ...
For interaction with its environment, a robot is required to learn models of objects and to perceive these models in the livestreams from its sensors. In this paper, we propose a ...
We propose a novel tracking framework called visual tracker sampler that tracks a target robustly by searching for the appropriate trackers in each frame. Since the real-world trac...