Performance of many state-of-the-art face recognition (FR) methods deteriorates rapidly, when large in size databases are considered. In this paper, we propose a novel clustering ...
We introduce a boosting framework to solve a classification problem with added manifold and ambient regularization costs. It allows for a natural extension of boosting into both s...
Nicolas Loeff, David A. Forsyth, Deepak Ramachandr...
A critical optimization in the domain of linear signal transforms, such as the discrete Fourier transform (DFT), is loop merging, which increases data locality and reuse and thus ...
Classical statistical learning theory studies the generalisation performance of machine learning algorithms rather indirectly. One of the main detours is that algorithms are studi...
Abstract. A dynamic visual search framework based mainly on innerscene similarity is proposed. Algorithms as well as measures quantifying the difficulty of search tasks are suggest...