In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
Identifying functionally important sites from biological sequences, formulated as a biological sequence labeling problem, has broad applications ranging from rational drug design ...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Abstract. Today, 3-D angiography volumes are routinely generated from rotational angiography sequences. In previous work [7], we have studied the precision reached by registering s...
Erwan Kerrien, Marie-Odile Berger, Eric Maurincomm...
: This paper deals with the effect of bit change errors on the linear complexity of finite sequences. Though a change in a single bit can cause a large change in linear complexity,...