Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
Thispaper presents a nonparametricregion competition algorithm which combines scale-space clustering and region competition to segment the image. It also proposes a formal and gen...
Experiments have shown [2] that we can only memorize images up to a certain complexity level, after which, instead of memorizing the image itself, we, sort of, memorize a probabil...
Thispaper presents a text word extraction algorithm that takes a set of bounding boxes of glyphs and their associated text lines of a given document andpartitions the glyphs into ...
Visualization users are increasingly in need of techniques for assessing quantitative uncertainty and error in the images produced. Statistical segmentation algorithms compute the...
Joe Michael Kniss, Robert L. Van Uitert Jr., Abrah...