We discuss how Case Based Reasoning (CBR) (see e.g. [1], [4]) philosophy of adaptation of some known situations to new similar ones can be realized in rough set framework [5] for c...
We present a generic objectness measure, quantifying how
likely it is for an image window to contain an object of
any class. We explicitly train it to distinguish objects with
a...
Pierre America, Robin Milner, Oscar Nierstrasz, Ma...
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...
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...