We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although estimating the object posterior probability density from few examples seems in...
Derek Hoiem, Rahul Sukthankar, Henry Schneiderman,...
In evolutionary robotics, controllers are often designed in simulation, then transferred onto the real system. Nevertheless, when no accurate model is available, controller transfe...
We present a semi-supervised machine-learning approach for the classification of adjectives into property- vs. relationdenoting adjectives, a distinction that is highly relevant f...
Acquiring knowledge has long been the major bottleneck preventing the rapid spread of AI systems. Manual approaches are slow and costly. Machine-learning approaches have limitatio...
In this paper we describe the first stage of a new learning system for object detection and recognition. For our system we propose Boosting [5] as the underlying learning technique...
Andreas Opelt, Michael Fussenegger, Axel Pinz, Pet...