There has been much interest in unsupervised learning of hierarchical generative models such as deep belief networks. Scaling such models to full-sized, high-dimensional images re...
Honglak Lee, Roger Grosse, Rajesh Ranganath, Andre...
In this paper, we present Human-Aided Computing, an approach that uses an electroencephalograph (EEG) device to measure the presence and outcomes of implicit cognitive processing,...
Noisy or distorted video/audio training sets represent constant challenges in automated identification and verification tasks. We propose the method of Mutual Interdependence An...
Abstract— In human-robot communication it is often important to relate robot sensor readings to concepts used by humans. We believe that access to semantic maps will make it poss...
Martin Persson, Tom Duckett, Christoffer Valgren, ...
This paper deals with a new interest points detector. Unlike most standard detectors which concentrate on the local shape of the signal, the main objective of this new operator is...