We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
We propose an approach for detecting objects in large-scale range datasets that combines bottom-up and top-down processes. In the bottom-up stage, fast-to-compute local descriptors...
Alexander Patterson, Philippos Mordohai, Kostas Da...
We present MiniCount, the first efficient sound and complete algorithm for finding maximally contained rewritings of conjunctive queries with count, using conjunctive views with c...
For the RISM A/II collection of musical incipits (short extracts of scores, taken from the beginning), we have established a ground truth based on the opinions of human experts. I...
Worms are arguably the most serious security threat facing the Internet. Seeking a detection technique that is both sufficiently efficient and accurate to enable automatic conta...
David Whyte, Evangelos Kranakis, Paul C. van Oorsc...