We propose a method to learn heterogeneous models of object classes for visual recognition. The training images contain a preponderance of clutter and learning is unsupervised. Ou...
We study a class of functional which can be used for matching objects which can be represented as mappings from a fixed interval, I, to some "feature space." This class o...
Extracting and processing information from web pages is an important task in many areas like constructing search engines, information retrieval, and data mining from the Web. Comm...
Milos Kovacevic, Michelangelo Diligenti, Marco Gor...
We introduce a new descriptor for images which allows the construction of efficient and compact classifiers with good accuracy on object category recognition. The descriptor is the...
Which one comes first: segmentation or recognition? We propose a unified framework for carrying out the two simultaneously and without supervision. The framework combines a fle...