We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
In pervasive computing environments, conditions are highly variable and resources are limited. In order to meet the needs of applications, systems must adapt dynamically to changi...
Farshad A. Samimi, Philip K. McKinley, Seyed Masou...
The assessment of a probability distribution associated with a Bayesian network is a challenging task, even if its topology is sparse. Special probability distributions based on t...
Interacting State Machines (ISMs) are used to model reactive systems and to express and verify their properties. They can be seen both as automata exchanging messages simultaneousl...
This paper presents a low-cost and practical approach to achieve basic input using a tactile cube-shaped object, augmented with a set of sensors, processor, batteries and wireless...
Kristof Van Laerhoven, Nicolas Villar, Albrecht Sc...