Abstract. We consider the problem of detecting a large number of different classes of objects in cluttered scenes. We present a learning procedure, based on boosted decision stumps...
Antonio B. Torralba, Kevin P. Murphy, William T. F...
We consider online learning in repeated decision problems, within the framework of a repeated game against an arbitrary opponent. For repeated matrix games, well known results esta...
Abstract. We present a new method for proving liveness and termination properties for fair concurrent programs, which does not rely on finding a ranking function or on computing th...
Parosh Aziz Abdulla, Bengt Jonsson, Ahmed Rezine, ...
Abstract. In this paper, we investigate how an IA network can be effectively encoded into the SAT domain. We propose two basic approaches to modelling an IA network as a CSP: one r...
Segmentation of ultrasound images is often a very challenging task due to speckle noise that contaminates the image. It is well known that speckle noise exhibits an asymmetric dis...
Gregory G. Slabaugh, Gozde B. Unal, Tong Fang, Mic...