We present a novel technique for image inpainting, the problem of filling-in missing image parts. Image inpainting is ill-posed and we adopt a probabilistic model-based approach ...
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
Accurate estimation of the tick length of a synchronous program is essential for efficient and predictable implementations that are devoid of timing faults. The techniques to dete...
Partha S. Roop, Sidharta Andalam, Reinhard von Han...
Given a finite set of words w1, . . . , wn independently drawn according to a fixed unknown distribution law P called a stochastic language, an usual goal in Grammatical Inference ...
In probabilistic grammatical inference, a usual goal is to infer a good approximation of an unknown distribution P called a stochastic language. The estimate of P stands in some cl...