In this paper we propose and evaluate an algorithm that learns a similarity measure for comparing never seen objects. The measure is learned from pairs of training images labeled ...
Quantitative evaluation and comparison of image segmentation algorithms is now feasible owing to the recent availability of collections of hand-labeled images. However, little att...
Identifying functionally important sites from biological sequences, formulated as a biological sequence labeling problem, has broad applications ranging from rational drug design ...
- Clustering of data is an important data mining application. One of the problems with traditional partitioning clustering methods is that they partition the data into hard bound n...
In this paper we propose a novel non-rigid volume registration based on discrete labeling and linear programming. The proposed framework reformulates registration as a minimal path...
Ben Glocker, Nikos Komodakis, Nikos Paragios, Geor...